<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yves Vanaubel</style></author><author><style face="normal" font="default" size="100%">Pascal Mérindol</style></author><author><style face="normal" font="default" size="100%">Jean-Jacques Pansiot</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Brief History of MPLS Usage in IPv6</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement Conference (PAM)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">6PE tunnels</style></keyword><keyword><style  face="normal" font="default" size="100%">IPv6</style></keyword><keyword><style  face="normal" font="default" size="100%">LSE Stack</style></keyword><keyword><style  face="normal" font="default" size="100%">MPLS</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2016</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recent researches have stated the fast deployment of IPv6. It&amp;nbsp;has been demonstrated that IPv6 grows much faster, being so more and more&amp;nbsp;adopted by both Internet service providers but also by servers and end-hosts.&amp;nbsp;In parallel, researches have been conducted to discover and assess the usage of&amp;nbsp;MPLS tunnels. Indeed, recent developments in the ICMP protocol make certain&lt;br /&gt;categories of MPLS tunnels transparent to traceroute probing. However, these&amp;nbsp;studies focus only on IPv4, where MPLS is strongly deployed.&lt;/p&gt;&lt;p&gt;In this paper, we provide a first look at how MPLS is used under IPv6&amp;nbsp;networks using traceroute data collected by CAIDA.&amp;nbsp;We have observed, at the first glance, that the MPLS deployment and usage seem to greatly differ between IPv4 and IPv6,&amp;nbsp;in particular in the way MPLS label stacks are used. While label stacks are not that frequent&amp;nbsp;in IPv4 (and mostly correspond to a VPN usage), they are prevalent in IPv6. &amp;nbsp;However, after a deeper look at the label stack typical content in IPv6, we understand that 2-label stack tunnels are mainly used for dual stack 6PE tunnels and ECMP load sharing purpose. &amp;nbsp;The technical deployment of such tunnels is really similar to VPN in practice but the objective is not the same (they are standard tunnels made with the IPv4 LDP for carrying IPv6 traffic).&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Donato Del Buono</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experimental investigation on TCP throughput behavior in Optical Fiber Access Networks</style></title><secondary-title><style face="normal" font="default" size="100%">Fiber and Integrated Optics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Journal article.</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Didier Colle</style></author><author><style face="normal" font="default" size="100%">Piet Demeester</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mixed-Integer Optimization for the Combined capacitated Facility Location-Routing Problem</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on the Design of Reliable Communication Networks (DRCN) 2016</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><publisher><style face="normal" font="default" size="100%">IEEE XPlore</style></publisher><pub-location><style face="normal" font="default" size="100%">Paris, France</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">H.Niedermayer</style></author><author><style face="normal" font="default" size="100%">B.Lannoo</style></author><author><style face="normal" font="default" size="100%">J.Rak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Understanding and modeling the inter-play between Sustainability, Resilience, and Robustness in networks</style></title><secondary-title><style face="normal" font="default" size="100%">Electronic Notes in Discrete Mathematics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><volume><style face="normal" font="default" size="100%">51</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Sarah Wassermann</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unveiling Network and Service Performance Degradation in the Wild with mPlane</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Communications Magazine - Network Testing Series</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Unveiling network and service performance issues in complex and highly decentralized systems such as the Internet is a major challenge. Indeed, the Internet is based on decentralization and diversity. However, its distributed nature leads to operational brittleness and difficulty in identifying the root causes of performance degradation. In such a context, network measurements are a fundamental pillar to shed light and to unveil design and implementation defects. To tackle this fragmentation and visibility problem, we have recently conceived mPlane, a distributed measurement platform which runs, collects and analyses traffic measurements to study the operation and functioning of the Internet. In this paper, we show the potentiality of the mPlane approach to unveil network and service degradation issues in live, operational networks, involving both fixed-line and cellular networks. In particular, we combine active and passive measurements to troubleshoot problems in end-customer Internet access connections, or to automatically detect and diagnose anomalies in Internet-scale services (e.g., YouTube) which impact a large number of end-users.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Martin Varela</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Helena Rivas</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the Analysis of QoE in Cellular Networks: from Subjective Tests to Large-scale Traffic Measurements</style></title><secondary-title><style face="normal" font="default" size="100%">6th International Workshop on Traffic Analysis and Characterization (TRAC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cicalese, Danilo</style></author><author><style face="normal" font="default" size="100%">Auge, Jordan</style></author><author><style face="normal" font="default" size="100%">Joumblatt, Diana</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author><author><style face="normal" font="default" size="100%">Friedman, Timur</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Anycast census and geolocation</style></title><secondary-title><style face="normal" font="default" size="100%">7th Workshop on Active Internet Measurements (AIMS 2015)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">April 2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15aims.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Lukasz Golab</style></author><author><style face="normal" font="default" size="100%">Stefan Ruehrup</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cache Oblivious Scheduling of Shared Workloads</style></title><secondary-title><style face="normal" font="default" size="100%">31st IEEE International Conference on Data Engineering (ICDE)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Seoul, Korea</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Shared workload optimization is feasible if the set of tasks to be executed is known in advance, as is the case in updating a set of materialized views or executing an extract-transform-load workflow. In this paper, we consider dataintensive shared workloads with precedence constraints arising from data dependencies, i.e., before executing some task, other tasks may have to run first and generate some data needed by the next task(s). While there has been previous work on identifying common subexpressions in shared workloads and task re-ordering to enable shared scans, in this paper we go a step further and solve the problem of scheduling shared data-intensive workloads in a cache-oblivious way. Our solution relies on a novel formulation of precedence constrained scheduling with the additional constraint that once a data item is in the cache, all tasks that require this data item should execute as soon as possible thereafter. The intuition behind this formulation is that the longer a data item remains in the cache, the more likely it is to be evicted regardless of the cache size. We give an optimal ordering algorithm using A* search over the space of possible orderings, and we propose efficient and effective heuristics that obtain nearly-optimal results in much less time. We present experimental results on real-life data warehouse workloads and the TCP-DS benchmark to validate our claims.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Faath</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Fabian Weisshaar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Cautious Look at Using Internet Standards-to-be in Research Work</style></title><secondary-title><style face="normal" font="default" size="100%">2015 IEEE Conference on Standards for Communications and Networking (CSCN) (CSCN'15)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">document lifecycle</style></keyword><keyword><style  face="normal" font="default" size="100%">ietf</style></keyword><keyword><style  face="normal" font="default" size="100%">RFCs</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Standardization of Internet protocols is usually a somewhat slow process. The reasons for this are manifold. Besides working out the protocol details, things like opposing stakeholder interests can prolong the consensus building process, new requirements might be introduced that require technical changes to the protocol, coordination across standards developing organizations (SDOs) might add delays just to name a few. For potential users of a standard-to-be, the time to specify and implement it often stalls progress on projects which could have been finished far earlier using proprietary - but ultimately non-interoperable - implementations. For research work, interoperability is however not always an important concern. The overhead and delay of an SDO in these cases is typically a hard to calculate risk for a research project. It represents an external dependency for the work but there is only a finite amount of funding and time to finish the project. On the other hand, using standardized technology increases the likelihood that the output of the project is being used by external parties after the lifetime of a research project and the implementation experience can be valuable input to the standardization process. In this paper, we analyze the lifecycle of recent Internet standards to provide researchers an insight into the Internet Engineering Task Force (IETF) standardization process duration. We evaluate different areas, document phases, working groups and other aspects of the standardization process. This allows researchers to better judge whether they want to employ standards-to-be in research work or engage with the IETF to specify protocols based on research prototypes.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Challenging Entropy-based Anomaly Detection and Diagnosis in Cellular Networks</style></title><secondary-title><style face="normal" font="default" size="100%">ACM SIGCOMM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cicalese, Danilo</style></author><author><style face="normal" font="default" size="100%">Auge, Jordan</style></author><author><style face="normal" font="default" size="100%">Joumblatt, Diana</style></author><author><style face="normal" font="default" size="100%">Friedman, Tim ur</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing IPv4 Anycast Adoption and Deployment</style></title><secondary-title><style face="normal" font="default" size="100%">ACM CoNEXT</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15conext.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Heidelberg, DE</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of TCP congestion control algorithms in data transfers on high RTT </style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis (TMA), Barcellona, 21-24 April 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Poster</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">A. Bakay</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">G. Rozsa</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">L. Baltrunas</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">Andrea Fregosi</style></author><author><style face="normal" font="default" size="100%">A. Kahveci</style></author><author><style face="normal" font="default" size="100%">Eike Kowallik</style></author><author><style face="normal" font="default" size="100%">G. Mattellini</style></author><author><style face="normal" font="default" size="100%">C. Meregalli</style></author><author><style face="normal" font="default" size="100%">Stefano Raffaglio</style></author><author><style face="normal" font="default" size="100%">M. Russo</style></author><author><style face="normal" font="default" size="100%">Andrea Sannino</style></author><author><style face="normal" font="default" size="100%">M. Scarpino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Demonstration Plan</style></title><short-title><style face="normal" font="default" size="100%">D6.1</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2015</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D6.1</style></number><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Bernard Fortz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed Monitoring Problem</style></title><secondary-title><style face="normal" font="default" size="100%">7th International Network Optimization Conference (INOC) 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Mirja Kühlewind</style></author><author><style face="normal" font="default" size="100%">Damiano Boppart</style></author><author><style face="normal" font="default" size="100%">Iain Learmonth</style></author><author><style face="normal" font="default" size="100%">Gorry Fairhurst</style></author><author><style face="normal" font="default" size="100%">Richard Scheffenegger</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enabling Internet-Wide Deployment of Explicit Congestion Notification</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2015 Passive and Active Measurement Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;\ac{ECN} is an TCP/IP extension to signal network congestion without packet loss, which has barely seen deployment though it was standardized and implemented more than a decade ago. On-going activities in research and standardization aim to make the usage of \ac{ECN} more beneficial. This measurement study provides an update on deployment status and newly assesses the marginal risk of enabling \ac{ECN} negotiation by default on client end-systems. Additionally, we dig deeper into causes of connectivity and negotiation issues linked to \ac{ECN}. We find that about five websites per thousand suffer additional connection setup latency when fallback per RFC 3168 is correctly implemented; we provide a patch for Linux to properly perform this fallback. Moreover, we detect and explore a number of cases in which \ac{ECN} brokenness is clearly path-dependent, i.e. on middleboxes beyond the access or content provider network. Further analysis of these cases can guide their elimination, further reducing the risk of enabling \ac{ECN} by default.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Mirja Kühlewind</style></author><author><style face="normal" font="default" size="100%">Damiano Boppart</style></author><author><style face="normal" font="default" size="100%">Iain Learmonth</style></author><author><style face="normal" font="default" size="100%">Gorry Fairhurst</style></author><author><style face="normal" font="default" size="100%">Richard Scheffenegger</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enabling Internet-Wide Deployment of Explicit Congestion Notification</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2015 Passive and Active Measurement Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Mar</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ecn.ethz.ch/ecn-pam15.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author><author><style face="normal" font="default" size="100%">Florian Wamser</style></author><author><style face="normal" font="default" size="100%">Michael Seufert</style></author><author><style face="normal" font="default" size="100%">Ralf Irmer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring QoE in Cellular Networks: How Much Bandwidth do you Need for Popular Smartphone Apps?</style></title><secondary-title><style face="normal" font="default" size="100%">5th ACM SIGCOMM Workshop on All Things Cellular: Operations, Applications and Challenges</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cicalese, Danilo</style></author><author><style face="normal" font="default" size="100%">Joumblatt, Diana</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author><author><style face="normal" font="default" size="100%">Buob, Marc-Olivier</style></author><author><style face="normal" font="default" size="100%">Auge, Jordan</style></author><author><style face="normal" font="default" size="100%">Friedman, Timur</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Fistful of Pings: Accurate and Lightweight Anycast Enumeration and Geolocation</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE INFOCOM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15infocom.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Use of IP-layer anycast has increased in the last few years: once relegated to DNS root and top-level domain servers, anycast is now commonly used to assist distribution of general purpose content by CDN providers. Yet, the measurement techniques for discovering anycast replicas have been designed around DNS, limiting their usefulness to this particular service. This raises the need for protocol agnostic methodologies, that should additionally be as lightweight as possible in order to scale up anycast service discovery. This is precisely the aim of this paper, which proposes a new method for exhaustive and accurate enumeration and city-level geolocation of anycast instances, requiring only a handful of latency measurements from a set of known vantage points. Our method exploits an iterative workflow that enumerates (an optimization problem) and geolocates (a classification problem) anycast replicas. We thoroughly validate our methodology on available ground truth (several DNS root servers), using multiple measurement infrastructures (PlanetLab, RIPE), obtaining extremely accurate results (even with simple algorithms, that we compare with the global optimum), that we make available to the scientific community. Compared to the state of the art work that appeared in INFOCOM 2013 and IMC 2013, our technique (i) is not bound to a specific protocol, (ii) requires 1000 times fewer vantage points, not only (iii) achieves over 50% recall but also (iv) accurately identifies the city-level geolocation for over 78% of the enumerated servers, with (v) a mean geolocation error of 361 km for all enumerated servers.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Faath</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A GLIMPSE of the Internet's Fabric</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Performance Evaluation Methodologies and Tools</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Berlin</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mario Pastorelli</style></author><author><style face="normal" font="default" size="100%">Damiano Carra</style></author><author><style face="normal" font="default" size="100%">Matteo Dell'Amico</style></author><author><style face="normal" font="default" size="100%">Pietro Michiardi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HFSP: Bringing size-based scheduling to Hadoop</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transaction on Cloud Computing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">G. Dimopoulos</style></author><author><style face="normal" font="default" size="100%">I. Leontiadis</style></author><author><style face="normal" font="default" size="100%">P. Barlet-Ros</style></author><author><style face="normal" font="default" size="100%">K. Papagiannaki</style></author><author><style face="normal" font="default" size="100%">P. Steenkiste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identifying the Root Cause of Video Streaming Issues on Mobile Devices</style></title><secondary-title><style face="normal" font="default" size="100%">CoNext</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bocchi, Enrico</style></author><author><style face="normal" font="default" size="100%">Safari, Ali</style></author><author><style face="normal" font="default" size="100%">Traverso, Stefano</style></author><author><style face="normal" font="default" size="100%">Finamore, Alessandro</style></author><author><style face="normal" font="default" size="100%">Di Gennaro, Valeria</style></author><author><style face="normal" font="default" size="100%">Mellia, Marco</style></author><author><style face="normal" font="default" size="100%">Munafo, Maurizio</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of Carrier-Grade NAT on Web Browsing</style></title><secondary-title><style face="normal" font="default" size="100%"> 6th International Workshop on TRaffic Analysis and Characterization (TRAC) - The paper won the BEST PAPER award</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15trac.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Dobrovnik, Croatia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Public IPv4 addresses are a scarce resource. While IPv6 adoption is lagging, Network Address Translation (NAT) technologies have been deployed over the last years to alleviate IPv4 exiguity and their high rental cost. In particular, Carrier- Grade NAT (CGN) is a well known solution to mask a whole ISP network behind a limited amount of public IP addresses, significantly reducing expenses. Despite its economical benefits, CGN can introduce connectiv- ity issues which have sprouted a considerable effort in research, development and standardization. However, to the best of our knowledge, little effort has been dedicated to investigate the impact that CGN deployment may have on users’ traffic. This paper fills the gap. We leverage passive measurements from an ISP network deploying CGN and, by means of the Jensen- Shannon divergence, we contrast several performance metrics considering customers being offered public or private addresses. In particular, we gauge the impact of CGN presence on users’ web browsing experience. Our results testify that CGN is a mature and stable technology as, if properly deployed, it does not harm users’ web browsing experience. Indeed, while our analysis lets emerge expected stochastic differences of certain indexes (e.g., the difference in the path hop count), the measurements related to the quality of users’ browsing are otherwise unperturbed. Interestingly, we also observe that CGN protects customers from unsolicited, often malicious, traffic.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Bernard Fortz</style></author><author><style face="normal" font="default" size="100%">Enrico Gorgone</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Lagrangian relaxation for the time-dependent combined network design and routing problem</style></title><secondary-title><style face="normal" font="default" size="100%">Communications (ICC), 2015 IEEE International Conference on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">allocation planning process</style></keyword><keyword><style  face="normal" font="default" size="100%">flow conservation constraints</style></keyword><keyword><style  face="normal" font="default" size="100%">integer programming</style></keyword><keyword><style  face="normal" font="default" size="100%">integer programming methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Lagrangian relaxation</style></keyword><keyword><style  face="normal" font="default" size="100%">linear programming</style></keyword><keyword><style  face="normal" font="default" size="100%">Maintenance engineering</style></keyword><keyword><style  face="normal" font="default" size="100%">multi-commodity capacitated fixed charge network design</style></keyword><keyword><style  face="normal" font="default" size="100%">network routing problem</style></keyword><keyword><style  face="normal" font="default" size="100%">Optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality of Service</style></keyword><keyword><style  face="normal" font="default" size="100%">Reliability</style></keyword><keyword><style  face="normal" font="default" size="100%">resource allocation</style></keyword><keyword><style  face="normal" font="default" size="100%">resource installation</style></keyword><keyword><style  face="normal" font="default" size="100%">Resource management</style></keyword><keyword><style  face="normal" font="default" size="100%">Routing</style></keyword><keyword><style  face="normal" font="default" size="100%">routing decision process</style></keyword><keyword><style  face="normal" font="default" size="100%">telecommunication network routing</style></keyword><keyword><style  face="normal" font="default" size="100%">telecommunication traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">time-dependent combined network design</style></keyword><keyword><style  face="normal" font="default" size="100%">traffic demands</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE XPlore</style></publisher><pub-location><style face="normal" font="default" size="100%">London, United-Kingdom</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cicalese, Danilo</style></author><author><style face="normal" font="default" size="100%">Joumblatt, Diana</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author><author><style face="normal" font="default" size="100%">Buob, Marc-Olivier</style></author><author><style face="normal" font="default" size="100%">Auge, Jordan</style></author><author><style face="normal" font="default" size="100%">Friedman, Timur</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Lightweight Anycast Enumeration and Geolocation</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE INFOCOM, Demo Session</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15infocom-b.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Hong Kong, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Several Internet services such as CDNs, DNS name servers, and sinkholes use IP-layer anycast to reduce user response times and increase robustness with respect to network failures and denial of service attacks. However, current geolocation tools fail with anycast IP addresses. In our recent work [1], we remedy to this by developing an anycast detection, enumeration, and geolocation technique based on a set of delay measurements from a handful of geographically distributed vantage points. The technique (i) detects if an IP is anycast, (ii) enumerates replicas by finding the maximum set of non-overlapping disks (i.e., areas centered around vantage points), and (iii) geolocates the replicas by solving a classification problem and assigning the server location to the most likely city. We propose to demo this technique. In particular, we visually show how to detect an anycast IP, enumerate its replicas, and geolocate them on a map. The demo allows to browse previously geolocated services, as well as to explore new targets on demand.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liao, Yongjun</style></author><author><style face="normal" font="default" size="100%">Du, Wei</style></author><author><style face="normal" font="default" size="100%">Leduc, Guy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Lightweight Network Proximity Service Based On Neighborhood Models</style></title><secondary-title><style face="normal" font="default" size="100%">22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux  (SCVT)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Luxembourg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper proposes a network proximity service&amp;nbsp;based on the neighborhood models used in recommender systems.&amp;nbsp;Unlike previous approaches, our service infers network proximity&amp;nbsp;without trying to recover the latency between network nodes. By&amp;nbsp;asking each node to probe a number of landmark nodes which&amp;nbsp;can be servers at Google, Yahoo and Facebook, etc., a simple&amp;nbsp;proximity measure is computed and allows the direct ranking&amp;nbsp;and rating of network nodes by their proximity to a target node.&amp;nbsp;The service is thus lightweight and can be easily deployed in&amp;nbsp;e.g. P2P and CDN applications. Simulations on existing datasets&amp;nbsp;and experiments with a deployment over PlanetLab showed&amp;nbsp;that our service achieves an accurate proximity inference that&amp;nbsp;is comparable to state-of-the-art latency prediction approaches,&amp;nbsp;while being much simpler.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Faath</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measurements with the Masses</style></title><secondary-title><style face="normal" font="default" size="100%">IRTF &amp; ISOC Research and Applications of Internet Measurements (RAIM) Workshop</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Seufert</style></author><author><style face="normal" font="default" size="100%">Florian Wamser</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Ralf Irmer</style></author><author><style face="normal" font="default" size="100%">Phuoc Tran-Gia</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the Monitoring of YouTube QoE in Cellular Networks from End-devices</style></title><secondary-title><style face="normal" font="default" size="100%">Seventh ACM S3 Workshop</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yves Vanaubel</style></author><author><style face="normal" font="default" size="100%">Pascal Mérindol</style></author><author><style face="normal" font="default" size="100%">Jean-Jacques Pansiot</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MPLS Under the Microscope: Revealing Actual Transit Path Diversity</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference (IMC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ECMP</style></keyword><keyword><style  face="normal" font="default" size="100%">LDP</style></keyword><keyword><style  face="normal" font="default" size="100%">MPLS</style></keyword><keyword><style  face="normal" font="default" size="100%">multipath</style></keyword><keyword><style  face="normal" font="default" size="100%">network discovery</style></keyword><keyword><style  face="normal" font="default" size="100%">RSVP-TE</style></keyword><keyword><style  face="normal" font="default" size="100%">traceroute</style></keyword><keyword><style  face="normal" font="default" size="100%">traffic engineering</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Traffic Engineering (TE) is one of the keys for improving packet forwarding in&amp;nbsp;the Internet. It allows IP network operators to finely tune their forwarding&amp;nbsp;paths according to various customer needs. One of the most popular tool&amp;nbsp;available today for optimizing the use of networking resources is MPLS. On the&amp;nbsp;one hand, operators may use MPLS and label distribution mechanisms such as RSVP-TE&amp;nbsp;in conjunction with BGP to define multiple transit paths (for a given edge pair)&lt;br /&gt;verifying different constraints on their network. On the other hand, when&amp;nbsp;operators simply enable LDP for distributing MPLS labels in order to improve the&amp;nbsp;scalability of their network, another kind of path diversity may appear thanks&amp;nbsp;to the ECMP feature of IGP routing.&lt;/p&gt;&lt;p&gt;In this paper, using an MPLS labels analysis, we demonstrate that it is possible&amp;nbsp;to better understand the transit path diversity deployed within a given ISP.&amp;nbsp;More specifically, we introduce the Label Pattern Recognition (LPR) algorithm, a&amp;nbsp;method for analyzing traceroute data including MPLS information. LPR reveals&amp;nbsp;the actual usage of MPLS according to the inferred label distribution protocol and&amp;nbsp;is able to make the distinction between ECMP and TE multi-path forwarding.&amp;nbsp;Based on an extensive and longitudinal traceroute dataset obtained from CAIDA,&lt;br /&gt;we apply LPR and find that each ISP behavior is really specific in regard to its&amp;nbsp;MPLS usage. In particular, we are able to observe independently for each ISP&amp;nbsp;the MPLS path diversity and usage, and its evolution over time.&amp;nbsp;Globally speaking, the main outcomes of our study are that (&lt;em&gt;i&lt;/em&gt;) the usage of&amp;nbsp;MPLS has been increasing over the the last five years with basic encapsulation&amp;nbsp;being predominant, (&lt;em&gt;ii&lt;/em&gt;) path diversity is mainly provided thanks to ECMP and&amp;nbsp;LDP, and, (&lt;em&gt;iii&lt;/em&gt;), TE using MPLS is as common as MPLS without path diversity.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Philippe Svoboda</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MTRAC - Discovering M2M Devices in Cellular Networks from Coarse-grained Measurements</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Conference on Communications (ICC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Naylor</style></author><author><style face="normal" font="default" size="100%">Kyle Schomp</style></author><author><style face="normal" font="default" size="100%">Matteo Varvello</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Jeremy Blackburn</style></author><author><style face="normal" font="default" size="100%">Diego Lopez</style></author><author><style face="normal" font="default" size="100%">Konstantina Papagiannaki</style></author><author><style face="normal" font="default" size="100%">Pablo Rodriguez</style></author><author><style face="normal" font="default" size="100%">Peter Steenkiste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">multi-context TLS (mcTLS): Enabling Secure In-Network Functionality in TLS</style></title><secondary-title><style face="normal" font="default" size="100%">2015 ACM SIGCOMM Conference (SIGCOMM ’15)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Transport Layer Security (TLS), is the de facto protocol supporting secure HTTP (HTTPS), and is being discussed as the default transport protocol for HTTP2.0. It has seen wide adoption and is currently carrying a significant fraction of the overall HTTP traffic (Facebook, Google and Twitter use it by default). However, TLS makes the fundamental assumption that all functionality resides solely at the endpoints, and is thus unable to utilize the many in-network services that optimize network resource usage, improve user experience, and protect clients and servers from security threats. Re-introducing such in-network functionality into secure TLS sessions today is done through hacks, in many cases weakening overall security.&lt;/p&gt;&lt;p&gt;In this paper we introduce multi-context TLS (mcTLS) which enhances TLS by allowing middleboxes to be fully supported participants in TLS sessions. mcTLS breaks the &quot;all-or-nothing&quot; security model by allowing endpoints and content providers to explicitly introduce middleboxes in secure end-to-end sessions, while deciding whether they should have read or write access, and to which specific parts of the content. mcTLS enables transparency and control for both clients and servers.&lt;/p&gt;&lt;p&gt;We evaluate a prototype mcTLS implementation in both controlled and &quot;live&quot; experiments, showing that the benefits offered have minimal overhead.More importantly, we show that mcTLS can be incrementally deployed and requires small changes to clients, servers, and middleboxes, for a large number of use cases.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Mirja Kuehlewind</style></author><author><style face="normal" font="default" size="100%">Elio Gubser</style></author><author><style face="normal" font="default" size="100%">Joe Hildebrand</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A New Transport Encapsulation for Middlebox Cooperation</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2015 IEEE Conference on Standards for Communications and Networking</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Davide Careglio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nonparametric Statistical Methods to Analyze the Internet Connectivity Reliability</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Conference on Communications Quality and Reliability (CQR 2015)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Mirja Kühlewind</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Observing Internet Path Transparency to Support Protocol Engineering</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the first IRTF/ISOC Workshop on Research and Applications of Internet Measurements (RAIM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fiadino, Pierdomenico</style></author><author><style face="normal" font="default" size="100%">Casas, Pedro</style></author><author><style face="normal" font="default" size="100%">Schiavone, Mirko</style></author><author><style face="normal" font="default" size="100%">D'Alconzo, Alessandro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks</style></title><secondary-title><style face="normal" font="default" size="100%">IFIP Networking Conference (IFIP Networking), 2015</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cellular Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Europe</style></keyword><keyword><style  face="normal" font="default" size="100%">Facebook</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">IP networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Network Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Online Social Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Organizations</style></keyword><keyword><style  face="normal" font="default" size="100%">Servers</style></keyword><keyword><style  face="normal" font="default" size="100%">WhatsApp</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Personal Cloud Storage Benchmarks and Comparison</style></title><secondary-title><style face="normal" font="default" size="100%">Cloud Computing, IEEE Transactions on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Benchmark testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud computing</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Computers</style></keyword><keyword><style  face="normal" font="default" size="100%">Google</style></keyword><keyword><style  face="normal" font="default" size="100%">Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Performance</style></keyword><keyword><style  face="normal" font="default" size="100%">Servers</style></keyword><keyword><style  face="normal" font="default" size="100%">Synchronization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><volume><style face="normal" font="default" size="100%">PP</style></volume><pages><style face="normal" font="default" size="100%">1-1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The large amount of space offered by personal cloud storage services (e.g., Dropbox and OneDrive), together with the possibility of synchronizing devices seamlessly, keep attracting customers to the cloud. Despite the high public interest, little information about system design and actual implications on performance is available when selecting a cloud storage service. Systematic benchmarks to assist in comparing services and understanding the effects of design choices are still lacking. This paper proposes a methodology to understand and benchmark personal cloud storage services. Our methodology unveils their architecture and capabilities. Moreover, by means of repeatable and customizable tests, it allows the measurement of performance metrics under different workloads. The effectiveness of the methodology is shown in a case study in which 11 services are compared under the same conditions. Our case study reveals interesting differences in design choices. Their implications are assessed in a series of benchmarks. Results show no clear winner, with all services having potential for improving performance. In some scenarios, the synchronization of the same files can take 20 times longer. In other cases, we observe a wastage of twice as much network capacity, questioning the design of some services. Our methodology and results are thus useful both as benchmarks and as guidelines for system design.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Personal Cloud Storage: Usage, Performance and Impact of Terminals </style></title><secondary-title><style face="normal" font="default" size="100%">4th IEEE International Conference on Cloud Networking (IEEE CloudNet 2015)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ieee-cloudnet.org/program.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Niagara Falls, Canada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Personal cloud storage services such as Dropbox and OneDrive are popular among Internet users. They help in sharing content and backing up data by relying on the cloud to store files. The rise of mobile terminals and the presence of new providers question whether the usage of cloud storage is evolving. This knowledge is essential to understand the workload these services need to handle, their performance, and implications. In this paper we present a comprehensive characterization of personal cloud storage services. Relying on traces collected for one month in an operational network, we show that users of each service present distinct behaviors. Dropbox is now threatened by competitors, with OneDrive and Google Drive reaching large market shares. However, the popularity of the latter services seems to be driven by their integration into Windows and Android. Indeed, around 50% of their users do not produce any workload. Considering performance, providers show distinct trade-offs, with bottlenecks that hardly allow users to fully exploit their access line bandwidth. Finally, usage of cloud services is now ordinary among mobile users, thanks to the automatic backup of pictures and media files.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">QoMOSN - On the Analysis of Traffic and Quality of Experience in Mobile Online Social Networks</style></title><secondary-title><style face="normal" font="default" size="100%">European Conference on Networks and Communications (EuCNC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Du, Wei</style></author><author><style face="normal" font="default" size="100%">Liao, Yongjun</style></author><author><style face="normal" font="default" size="100%">Tao, Narisu</style></author><author><style face="normal" font="default" size="100%">Geurts, Pierre</style></author><author><style face="normal" font="default" size="100%">Fu, Xiaoming</style></author><author><style face="normal" font="default" size="100%">Leduc, Guy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Rating Network Paths for Locality-Aware Overlay Construction and Routing</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE/ACM Transactions on Networking</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">matrix factorization</style></keyword><keyword><style  face="normal" font="default" size="100%">network inference</style></keyword><keyword><style  face="normal" font="default" size="100%">rating-based network measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">recommender system</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">23</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper investigates the rating of network paths,&amp;nbsp;i.e. acquiring quantized measures of path properties such as&amp;nbsp;round-trip time and available bandwidth. Comparing to finegrained&amp;nbsp;measurements, coarse-grained ratings are appealing in&amp;nbsp;that they are not only informative but also cheap to obtain.&lt;/p&gt;&lt;p&gt;Motivated by this insight, we firstly address the scalable&amp;nbsp;acquisition of path ratings by statistical inference. By observing&amp;nbsp;similarities to recommender systems, we examine the applicability&amp;nbsp;of solutions to recommender system and show that our&amp;nbsp;inference problem can be solved by a class of matrix factorization&amp;nbsp;techniques. A technical contribution is an active and progressive&amp;nbsp;inference framework that not only improves the accuracy by&amp;nbsp;selectively measuring more informative paths but also speeds&amp;nbsp;up the convergence for available bandwidth by incorporating its&amp;nbsp;measurement methodology.&lt;/p&gt;&lt;p&gt;Then, we investigate the usability of rating-based network&amp;nbsp;measurement and inference in applications. A case study is&amp;nbsp;performed on whether locality awareness can be achieved for&amp;nbsp;overlay networks of Pastry and BitTorrent using inferred ratings.&lt;/p&gt;&lt;p&gt;We show that such coarse-grained knowledge can improve the&amp;nbsp;performance of peer selection and that finer granularities do not&amp;nbsp;always lead to larger improvements.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><section><style face="normal" font="default" size="100%">1661</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">RCATool - A Framework for Detecting and Diagnosing Anomalies in Cellular Networks</style></title><secondary-title><style face="normal" font="default" size="100%">27th International Teletraffic Congress (ITC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Bernard Fortz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Robust cooperative monitoring problem</style></title><secondary-title><style face="normal" font="default" size="100%">Reliable Networks Design and Modeling (RNDM), 2015 7th International Workshop on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">box+ellipsoidal perturbation set</style></keyword><keyword><style  face="normal" font="default" size="100%">box+polyhedral perturbation set</style></keyword><keyword><style  face="normal" font="default" size="100%">cooperative communication</style></keyword><keyword><style  face="normal" font="default" size="100%">integer programming</style></keyword><keyword><style  face="normal" font="default" size="100%">linear programming</style></keyword><keyword><style  face="normal" font="default" size="100%">MILP</style></keyword><keyword><style  face="normal" font="default" size="100%">Minimization</style></keyword><keyword><style  face="normal" font="default" size="100%">mixed-integer linear program</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">passive monitoring point configuration</style></keyword><keyword><style  face="normal" font="default" size="100%">passive monitoring point placement</style></keyword><keyword><style  face="normal" font="default" size="100%">robust cooperative monitoring problem</style></keyword><keyword><style  face="normal" font="default" size="100%">Robustness</style></keyword><keyword><style  face="normal" font="default" size="100%">Routing</style></keyword><keyword><style  face="normal" font="default" size="100%">telecommunication traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">time-varying traffic flow monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Topology</style></keyword><keyword><style  face="normal" font="default" size="100%">Uncertainty</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Papadimitriou, D.</style></author><author><style face="normal" font="default" size="100%">Fortz, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Robust cooperative monitoring problem</style></title><secondary-title><style face="normal" font="default" size="100%">Reliable Networks Design and Modeling (RNDM), 2015 7th International Workshop on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">box+ellipsoidal perturbation set</style></keyword><keyword><style  face="normal" font="default" size="100%">box+polyhedral perturbation set</style></keyword><keyword><style  face="normal" font="default" size="100%">cooperative communication</style></keyword><keyword><style  face="normal" font="default" size="100%">integer programming</style></keyword><keyword><style  face="normal" font="default" size="100%">linear programming</style></keyword><keyword><style  face="normal" font="default" size="100%">MILP</style></keyword><keyword><style  face="normal" font="default" size="100%">Minimization</style></keyword><keyword><style  face="normal" font="default" size="100%">mixed-integer linear program</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">passive monitoring point configuration</style></keyword><keyword><style  face="normal" font="default" size="100%">passive monitoring point placement</style></keyword><keyword><style  face="normal" font="default" size="100%">robust cooperative monitoring problem</style></keyword><keyword><style  face="normal" font="default" size="100%">Robustness</style></keyword><keyword><style  face="normal" font="default" size="100%">Routing</style></keyword><keyword><style  face="normal" font="default" size="100%">telecommunication traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">time-varying traffic flow monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Topology</style></keyword><keyword><style  face="normal" font="default" size="100%">Uncertainty</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Bernard Fortz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Robust Cooperative Monitoring Problem</style></title><secondary-title><style face="normal" font="default" size="100%">7th International Workshop on Reliable Networks Design and Modeling (RNDM) 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE XPlore</style></publisher><pub-location><style face="normal" font="default" size="100%">Munich, Germany</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Elena Mammi</style></author><author><style face="normal" font="default" size="100%">Ariana Rufini</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SLA verification and certification, Traffic Monitoring and Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis (TMA), Barcellona, 21-25 April 2015.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Poster</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hadrien Hours</style></author><author><style face="normal" font="default" size="100%">Ernst Biersack</style></author><author><style face="normal" font="default" size="100%">Patrick Loiseau</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Study of the Impact of DNS Resolvers on Performance Using a Causal Approach</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Teletraffic Congress</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNS</style></keyword><keyword><style  face="normal" font="default" size="100%">reasoner</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Ghent, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For a user to access any resource on the Internet, it is necessary to first locate a server hosting the requested resource. The Domain Name System service (DNS) represents the first step in this process, translating a human readable name, the resource host name, into an IP address. With the expansion of Content Distribution Networks (CDNs), the DNS service has seen its importance increase. In a CDN, objects are replicated on different servers to decrease the distance from the client to a server hosting the object that needs to be accessed. The DNS service should improve user experience by directing its demand to the optimal CDN server. While most of the Internet Service Providers (ISPs) offer a DNS service to their customers, it is now common to see clients using a public DNS service instead. This choice may have an impact on Web browsing performance. In this paper we study the impact of choosing one DNS server instead of another and we compare the performance of a large European ISP DNS service with the one of a public DNS service, Google DNS. We propose a causal approach to expose the structural dependencies of the different parameters impacted by the DNS service used and we show how to model these dependencies with a Bayesian network. This model allows us to explain and quantify the benefits obtained by clients using their ISP DNS service and to propose a solution to further improve their performance.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P Casas</style></author><author><style face="normal" font="default" size="100%">B Gardlo</style></author><author><style face="normal" font="default" size="100%">M Seufert</style></author><author><style face="normal" font="default" size="100%">F Wamser</style></author><author><style face="normal" font="default" size="100%">R Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field</style></title><secondary-title><style face="normal" font="default" size="100%">IRTF &amp; ISOC Workshop on  Research and Applications of Internet Measurements (RAIM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P Casas</style></author><author><style face="normal" font="default" size="100%">B Gardlo</style></author><author><style face="normal" font="default" size="100%">M Seufert</style></author><author><style face="normal" font="default" size="100%">F Wamser</style></author><author><style face="normal" font="default" size="100%">R Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field</style></title><secondary-title><style face="normal" font="default" size="100%">11th International Conference on Network and Service Management (CNSM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Korian Edeline</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards a Middlebox Policy Taxonomy: Path Impairments</style></title><secondary-title><style face="normal" font="default" size="100%">International Workshop on Network Science for Communication Networks (NetSciCom)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">IPv6</style></keyword><keyword><style  face="normal" font="default" size="100%">middleboxes</style></keyword><keyword><style  face="normal" font="default" size="100%">path impairment</style></keyword><keyword><style  face="normal" font="default" size="100%">tracebox</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recent years have seen the rise of middleboxes, such as firewalls, NATs, proxies,&amp;nbsp;or Deep Packet Inspectors. Those middleboxes play an important role in today's&amp;nbsp;Internet, including enterprise networks and cellular networks. However, despite&amp;nbsp;their huge success in modern network architecture, they have a negative impact&amp;nbsp;on the Internet evolution as they can slow down the TCP protocol evolution and its&amp;nbsp;extensions. Making available a summary of the potential middlebox network&amp;nbsp;interferences is of the highest importance as it could allow researchers to&amp;nbsp;confront their new transport protocol to potential issues caused by middleboxes.&amp;nbsp;And, consequently, allowing again innovation in the Internet.&lt;/p&gt;&lt;p&gt;This is exactly what we tackle in this paper. We propose a path impairment&amp;nbsp;oriented middlebox taxonomy that aims at categorizing the initial purpose of a&amp;nbsp;middlebox policy as well as its potential unexpected complications. Based on a&amp;nbsp;measurement campaign on IPv4 and IPv6 networks, we confront our taxonomy to the&amp;nbsp;real world. Our dataset is freely available.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards Automatic Detection and Diagnosis of Internet Service Anomalies via DNS Traffic Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">6th International Workshop on Traffic Analysis and Characterization (TRAC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sarah Wassermann</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards DisNETPerf: a Distributed Internet Paths Performance Analyzer</style></title><secondary-title><style face="normal" font="default" size="100%">The 11th International Conference on emerging Networking EXperiments and Technologies - CoNEXT 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;For more than 25 years now, traceroute has demonstrated its supremacy for network-path measurement, becoming the most widely used Internet path diagnosis tool today. A major limitation of traceroute when the destination is not controllable by the user is its inability to measure reverse paths, i.e., the path from a destination back to the source. Proposed techniques to address this issue &amp;nbsp;rely on IP address spoofing, which might lead to security concerns. In this paper we introduce and evaluate DisNETPerf, a new tool for locating probes that are the closest to a distant server. Those probes are then used to collect data from the server point-of-view to the service user for path performance monitoring and troubleshooting purposes. We propose two techniques for probe location, and demonstrate that the reverse path can be measured with very high accuracy in certain scenarios.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Valentin Thirion</style></author><author><style face="normal" font="default" size="100%">Korian Edeline</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tracking Middleboxes in the Mobile World with TraceboxAndroid</style></title><secondary-title><style face="normal" font="default" size="100%">7th International Workshop on Traffic Monitoring and Analysis (TMA)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Android</style></keyword><keyword><style  face="normal" font="default" size="100%">tracebox</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2015</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Middleboxes are largely deployed over cellular networks. It is known that they&amp;nbsp;might disrupt network performance, expose users to security issues, and harm&amp;nbsp;protocols deployability. Further, hardly any network measurements tools for&amp;nbsp;smartphones are able to infer middlebox behaviors, specially if one cannot&amp;nbsp;control both ends of a path. In this paper, we present TraceboxAndroid a&lt;br /&gt;proof-of-concept measurement application for Android mobile devices&amp;nbsp;implementing the tracebox algorithm. It aims at diagnosing middlebox-impaired&amp;nbsp;paths by detecting and locating rewriting middleboxes. We analyze a dataset&amp;nbsp;sample to highlight the range of opportunities offered by TraceboxAndroid. We&amp;nbsp;show that TraceboxAndroid can be useful for mobile users as well as for the&lt;br /&gt;research community.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Troubleshooting Web Sessions with CUSUM</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Florian Wamser</style></author><author><style face="normal" font="default" size="100%">Michael Seufert</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Ralf Irmer</style></author><author><style face="normal" font="default" size="100%">Phuoc Tran-Gia</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Understanding YouTube QoE in Cellular Networks with YoMoApp - a QoE Monitoring Tool for YouTube Mobile</style></title><secondary-title><style face="normal" font="default" size="100%">ACM MOBICOM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fiadino, Pierdomenico</style></author><author><style face="normal" font="default" size="100%">Schiavone, Mirko</style></author><author><style face="normal" font="default" size="100%">Casas, Pedro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vivisecting WhatsApp in Cellular Networks: Servers, Flows, and Quality of Experience</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cellular Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Large-Scale Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality of Experience</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic characterization</style></keyword><keyword><style  face="normal" font="default" size="100%">WhatsApp</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-17172-2_4</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><isbn><style face="normal" font="default" size="100%">978-3-319-17171-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Konstantin Kutzkov</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Sofia Nikitaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Weighted Similarity Estimation in Data Streams</style></title><secondary-title><style face="normal" font="default" size="100%">CIKM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Similarity computation between pairs of objects is often a bottleneck in many applications that have to deal with massive volumes of data. Motivated by applications such as collaborative filtering in large-scale recommender systems, and influence probabilities learning in social networks, we present new randomized algorithms for the estimation of weighted similarity in data streams.&lt;/p&gt;&lt;p&gt;&lt;span style=&quot;font-size: 12.1599998474121px; line-height: 20.6719989776611px;&quot;&gt;Previous works have addressed the problem of learning binary similarity measures in a streaming setting. To the best of our knowledge, the algorithms proposed here are the first that specifically address the estimation of weighted similarity in data streams. The algorithms need only one pass over the data, making them ideally suited to handling massive data streams in real time.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span style=&quot;font-size: 12.1599998474121px; line-height: 20.6719989776611px;&quot;&gt; We obtain precise theoretical bounds on the approximation error and complexity of the algorithms. The results of evaluating our algorithms on two real-life datasets validate the theoretical findings and demonstrate the applicability of the proposed algorithms.&lt;/span&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Florian Wamser</style></author><author><style face="normal" font="default" size="100%">Michael Seufert</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Ralf Irmer</style></author><author><style face="normal" font="default" size="100%">Phuoc Tran-Gia</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YoMoApp: a Tool for Analyzing QoE of YouTube HTTP Adaptive Streaming in Mobile Networks</style></title><secondary-title><style face="normal" font="default" size="100%">European Conference on Networks and Communications (EuCNC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Seufert</style></author><author><style face="normal" font="default" size="100%">Florian Wamser</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Ralf Irmer</style></author><author><style face="normal" font="default" size="100%">Phuoc Tran-Gia</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming</style></title><secondary-title><style face="normal" font="default" size="100%">6th International Workshop on Traffic Analysis and Characterization (TRAC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Espinet, François</style></author><author><style face="normal" font="default" size="100%">Joumblatt, Diana</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Zen and the art of network troubleshooting: a hands on experimental study</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi15tma.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Growing network complexity necessitates tools and methodologies to automate network troubleshooting. In this paper, we follow a crowd-sourcing trend, and argue for the need to deploy measurement probes at end-user devices and gateways, which can be under the control of the users or the ISP. Depending on the amount of information available to the probes (e.g., ISP topology), we formalize the network troubleshooting task as either a clustering or a classification problem, that we solve with an algorithm that (i) achieves perfect classification under the assumption of a strategic selection of probes (e.g., assisted by an ISP) and (ii) operates blindly with respect to the network performance metrics, of which we consider delay and bandwidth in this paper. While previous work on network troubleshooting privileges a more theoretical vs practical approaches, our workflow balances both aspects as (i) we conduct a set of controlled experiments with a rigorous and reproducible methodology, (ii) on an emulator that we thoroughly calibrate, (iii) contrasting experimental results affected by real-world noise with expected results from a probabilistic model.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Edion Tego</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Active measurements and limitations of TCP protocol during SLA test</style></title><secondary-title><style face="normal" font="default" size="100%">Poster session the Sixth Workshop on Traffic and Monitoring Analysis (TMA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Colabrese, Silvia</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author><author><style face="normal" font="default" size="100%">Mellia, Marco</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Aggregation of Statistical Data from Passive Probes: Techniques and Best Practices</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Data aggregation</style></keyword><keyword><style  face="normal" font="default" size="100%">data reduction</style></keyword><keyword><style  face="normal" font="default" size="100%">scalability problem</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-54999-1_4</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><volume><style face="normal" font="default" size="100%">8406</style></volume><pages><style face="normal" font="default" size="100%">38-50</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-54998-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Passive probes continuously generate statistics on large number of metrics, that are possibly represented as probability mass functions (pmf). The need for consolidation of several pmfs arises in two contexts, namely: (i) whenever a central point collects and aggregates measurement of multiple disjoint vantage points, and (ii) whenever a local measurement processed at a single vantage point needs to be distributed over multiple cores of the same physical probe, in order to cope with growing link capacity. In this work, we take an experimental approach and study both cases using, whenever possible, open source software and datasets. Considering different consolidation strategies, we assess their accuracy in estimating pmf deciles (from the 10th to the 90th) of diverse metrics, obtaining general design and tuning guidelines. In our dataset, we find that Monotonic Spline Interpolation over a larger set of percentiles (e.g., adding 5th, 10th, 15th, and so on) allow fairly accurate pmf consolidation in both the multiple vantage points (median error is about 1%, maximum 30%) and local processes (median 0.1%, maximum 1%) cases.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Saverio Niccolini</style></author><author><style face="normal" font="default" size="100%">Sofia Nikitaki</style></author><author><style face="normal" font="default" size="100%">Daniele Apiletti</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">V, Guchev</style></author><author><style face="normal" font="default" size="100%">Zied Ben Houidi</style></author><author><style face="normal" font="default" size="100%">Pietro Michiardi</style></author><author><style face="normal" font="default" size="100%">Marco Milanesio</style></author><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">G, Dimopoulos</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">A, Bakay</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Algorithm and Scheduler Design and Implementation</style></title><short-title><style face="normal" font="default" size="100%">D3.3</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithm design</style></keyword><keyword><style  face="normal" font="default" size="100%">job scheduler</style></keyword><keyword><style  face="normal" font="default" size="100%">mPlane software</style></keyword><keyword><style  face="normal" font="default" size="100%">repository tools</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><isbn><style face="normal" font="default" size="100%">D3.3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the Analysis of QoE-based Performance Degradation in YouTube Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">10th International Conference on Network and Service Management, CNSM 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Empirical Entropy</style></keyword><keyword><style  face="normal" font="default" size="100%">Performance Degradation</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality of Experience</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Rio de Janeiro, Brazil</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;YouTube is the most popular service in today's Internet. Google relies on its massive Content Delivery Network (CDN) to push YouTube videos as close as possible to the end-users to improve their Quality of Experience (QoE), as well as to pursue its own optimization goals. Adopting space and time variant traffic delivery policies, Google servers handle users' requests from multiple geo-distributed locations at different times. Such traffic delivery policies can have a relevant impact on the traffic routed through the Internet Service Providers (ISPs) providing the access, but most importantly, they can have negative effects on the end-user QoE. In this paper we shed light on the problem of diagnosing QoE-based performance degradation events in YouTube's traffic. Through the analysis of one month of YouTube flow traces collected at the network of a large European ISP, we particularly identify and drill down a Google's CDN server selection policy negatively impacting the watching experience of YouTube users during several days at peak-load times. The analysis combines both the user-side perspective and the CDN perspective of the end-to-end YouTube delivery service to diagnose the problem. On the one hand, we rely on the monitoring of YouTube QoE-based Key Performance Indicators (KPIs) to detect performance degradation events affecting the end-customers. On the other hand, we analyze the temporal behavior of the Google CDN traffic delivery policies, by tracking the activity of the Google servers providing the videos. The analysis is supported by time-series analysis, entropy-based approaches, and clustering techniques to flag the aforementioned anomaly. The main contributions of the paper are threefold: firstly, we provide a large-scale characterization of the YouTube service in terms of traffic characteristics and provisioning behavior of the Google CDN servers. Secondly, we introduce simple yet effective QoE-based KPIs to monitor YouTube videos from the end-user perspective. Finally and most important, we analyze and provide evidence of the occurrence of QoE-based YouTube anomalies induced by CDN server selection policies, which are somehow normally hidden from the common knowledge of the end-user. This is a main issue for ISPs, who see their reputation degrade when such events occur, even if Google is the culprit.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Imbrenda, Claudio</style></author><author><style face="normal" font="default" size="100%">Muscariello, Luca</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analyzing Cacheable Traffic in ISP Access Networks for Micro CDN applications via Content-Centric Networking</style></title><secondary-title><style face="normal" font="default" size="100%">ACM SIGCOMM Information Centric Networks (ICN)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi14icn-c.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Paris, FR</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arianna Rufini</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bandwidth Measurements and Capacity Exploitation in Gigabit Passive Optical Networks</style></title><secondary-title><style face="normal" font="default" size="100%">Fotonica 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">access capacity</style></keyword><keyword><style  face="normal" font="default" size="100%">GPON</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE</style></keyword><keyword><style  face="normal" font="default" size="100%">QoS</style></keyword><keyword><style  face="normal" font="default" size="100%">Throughput</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We report an experimental investigation on the &lt;br /&gt;measurement of the available bandwidth for users in Gigabit &lt;br /&gt;Passive Optical Networks (GPON) and the limitations caused by &lt;br /&gt;the Internet protocols. We point out that the huge capacity &lt;br /&gt;offered by the GPON highlights the enormous differences that &lt;br /&gt;can be showed among the available and actually exploitable &lt;br /&gt;bandwidth in the case of TCP. In this ultrabroadband &lt;br /&gt;environment we also investigated on use of the UDP and of the&lt;br /&gt;multisession TCP. A correlation in terms of QoE is also reported.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Andreas Sackl</style></author><author><style face="normal" font="default" size="100%">Sebastian Egger</style></author><author><style face="normal" font="default" size="100%">Raimund Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing Microsoft Lync Online in Mobile Networks: a Quality of Experience Perspective</style></title><secondary-title><style face="normal" font="default" size="100%">3rd IEEE International Conference on Cloud Networking</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Audioconferencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud QoE</style></keyword><keyword><style  face="normal" font="default" size="100%">Distributed Data Center</style></keyword><keyword><style  face="normal" font="default" size="100%">Microsoft Lync Online</style></keyword><keyword><style  face="normal" font="default" size="100%">MOS</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote Desktop Sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">Telepresence</style></keyword><keyword><style  face="normal" font="default" size="100%">Videoconferencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Luxembourg, Luxembourg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cloud-based systems are gaining enormous popularity due to a number of promised benefits, including ease of deployment and administration, scalability and flexibility, and costs savings. However, as more personal and business applications migrate to the Cloud, the service quality becomes an important differentiator between providers. ISPs, Cloud providers and enterprises migrating their services to the Cloud must therefore understand the network requirements to ensure proper end-user Quality of Experience (QoE) in these services. This paper addresses the problem of QoE in Telepresence and Remote Collaboration (TRC) services provided by Microsoft Lync Online (MLO). MLO is a Cloud-based service providing online meeting capabilities including videoconferencing, audio calls, and desktop sharing, and has become the default system for TRC in enterprise scenarios. We present a complete study of the QoE undergone by 44 MLO users in controlled subjective lab tests. The study is performed on three different interactive scenarios running on top of the real MLO Cloud service, additionally shaping the Lync flows at the access network to influence the participants experience. The scenarios include audioconferencing, videoconferencing, and remote collaboration though desktop sharing. By passively monitoring the end-to-end QoS achieved by the Lync flows, and correlating it with the QoE feedbacks provided by the participants, this study permits to better understand the interplays between network performance and QoE in TRC Cloud services. In addition, we provide a network-level characterization of the traffic generated by MLO, as well as an overview on the infrastructure hosting MLO servers.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D’Alconzo</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing Web Services Provisioning via CDNs: The Case of Facebook</style></title><secondary-title><style face="normal" font="default" size="100%">5th International Workshop on TRaffic Analysis and Characterization</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Akamai</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Facebook</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">mobile networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Nicosia, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Today’s Internet consists of massive scale web&amp;nbsp;services and Content Delivery Networks (CDNs). This paper sheds&amp;nbsp;light on the way major Internet-scale web services content is&amp;nbsp;hosted and delivered. By analyzing a full month of HTTP traffic&amp;nbsp;traces collected at the mobile network of a major European ISP,&amp;nbsp;we characterize the paradigmatic case of Facebook, considering&amp;nbsp;not only the traffic flows but also the main organizations and&amp;nbsp;CDNs providing them. Our study serves the main purpose of&amp;nbsp;better understanding how major web services are provisioned&amp;nbsp;in today’s Internet, paying special attention to the temporal&amp;nbsp;dynamics of the service delivery and the interplays between the&amp;nbsp;involved hosting organizations. To the best of our knowledge, this&amp;nbsp;is the first paper providing such an analysis in mobile networks.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Sofiane Sarni</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cloud Storage Service Benchmarking: Methodologies and Experimentations</style></title><secondary-title><style face="normal" font="default" size="100%">3rd IEEE International Conference on Cloud Networking (IEEE CloudNet 2014)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amazon S3</style></keyword><keyword><style  face="normal" font="default" size="100%">Benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Performance measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">Web services</style></keyword><keyword><style  face="normal" font="default" size="100%">Windows Azure</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Luxembourg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 1&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;Data storage is one of today’s fundamental services with companies, universities and research centers having the need of storing large amounts of data every day. Cloud storage services are emerging as strong alternative to local storage, allowing customers to save costs of buying and maintaining expensive hardware. Several solutions are available on the market, the most famous being Amazon S3. However it is rather difficult to access information about each service architecture, performance, and pricing. To shed light on storage services from the customer perspective, we propose a benchmarking methodology, apply it to four popular offers (Amazon S3, Amazon Glacier, Windows Azure Blob and Rackspace Cloud Files), and compare their performance. Each service is analysed as a black box and benchmarked through crafted workloads. We take the perspective of a customer located in Europe, looking for possible service providers and the optimal data center where to deploy its applications. At last, we complement the analysis by comparing the actual and forecast costs faced when using each service. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;According to collected results, all services show eventual weaknesses related to some workload, with no all-round eligible winner, e.g., some offers providing excellent or poor performance when exchanging large or small files. For all services, it is of paramount importance to accurately select the data center to where deploy the applications, with throughput that varies by factors from 2x to 10x. The methodology (and tools implementing it) here presented is instrumental for potential customers to identify the most suitable offer for their needs.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Naylor</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Kostantina Papagiannaki</style></author><author><style face="normal" font="default" size="100%">Peter Steenkiste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Cost of the “S” in HTTPS</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Conference on emerging Networking EXperiments and Technologies (CoNEXT)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Umberto Manferdini</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Zied Ben Houidi</style></author><author><style face="normal" font="default" size="100%">Marco Milanesio</style></author><author><style face="normal" font="default" size="100%">Pietro Michiardi</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">D. Cicalese</style></author><author><style face="normal" font="default" size="100%">D. Joumblatt</style></author><author><style face="normal" font="default" size="100%">Jordan Augé</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Sofia Nikitaki</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">L. Baltrunas</style></author><author><style face="normal" font="default" size="100%">M. Varvello</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author><author><style face="normal" font="default" size="100%">W. Du</style></author><author><style face="normal" font="default" size="100%">Guy Leduc</style></author><author><style face="normal" font="default" size="100%">Y. Liao</style></author><author><style face="normal" font="default" size="100%">Alessandro Capello</style></author><author><style face="normal" font="default" size="100%">Fabrizio Invernizzi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%"> Cross-check of Analysis Modules and Reasoner Interactions</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">reasoner</style></keyword><keyword><style  face="normal" font="default" size="100%">WP4</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D4.3</style></number><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arian Baer</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Lukasz Golab</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DBStream: an Online Aggregation, Filtering and Processing System for Network Trafﬁc Monitoring</style></title><secondary-title><style face="normal" font="default" size="100%">TRAC</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Nicosia, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Claudio Testa</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Delay-based congestion control: Flow vs. BitTorrent swarm perspectives</style></title><secondary-title><style face="normal" font="default" size="100%">Elsevier Computer Networks</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi14comnet-a.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">60</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;BitTorrent, one of the most widespread file-sharing P2P applications, recently introduced LEDBAT, a novel congestion control protocol aiming at (i) limiting the additional delay due to queuing, to reduce interference with the rest of user traffic (e.g., Web, VoIP and gaming) sharing the same access bottleneck, and (ii) efficiently using the available link capacity, to provide users with good BitTorrent performance at the same time. In this work, we adopt two complementary perspectives: namely, a flow viewpoint to assess the Quality of Service (QoS) as in classic congestion control studies, and a BitTorrent swarm viewpoint to assess peer-to-peer users Quality of Experience (QoE). We additionally point out that congestion control literature is rich of protocols, such as VEGAS, LP, and NICE sharing similarities with LEDBAT, that is therefore mandatory to consider in the analysis. Hence, adopting the above viewpoints we both (i) contrast LEDBAT to the other protocols and (ii) provide deep understanding of the novel protocol and its implication on QoS and QoE. Our simulation based investigation yields several insights. At flow-level, we gather LEDBAT to be lowest priority among all protocols, which follows from its design that strives to explicitly bound the queuing delay at the bottleneck link to a maximum target value. At the same time, we see that this very same protocol parameter can be exploited by adversaries, that can set a higher target to gain an unfair advantage over competitors. Interestingly, swarm-level performance exhibit an opposite trade-off, with smaller targets being more advantageous for QoE of BitTorrent users. This can be explained with the fact that larger delay targets slow down BitTorrent signaling task, with possibly negative effect on the swarming protocol efficiency. Additionally, we see that for the above reason, in heterogeneous swarms, any delay-based protocol (i.e., not only LEDBAT but also VEGAS or NICE) can yield a competitive QoE advantage over loss-based TCP. Overall this tension between swarm and flow-levels suggests that, at least in current ADSL/cable access bottleneck scenarios, a safe LEDBAT operational point may be used in practice. At the same time, our results also point out that benefits similar to LEDBAT can also be gathered with other delay-based protocols such as VEGAS or NICE.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">115 -- 128</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Sofia Nikitaki</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Daniele Apiletti</style></author><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">D. Joumblatt</style></author><author><style face="normal" font="default" size="100%">Alessandro Capello</style></author><author><style face="normal" font="default" size="100%">M. D'Ambrosio</style></author><author><style face="normal" font="default" size="100%">Fabrizio Invernizzi</style></author><author><style face="normal" font="default" size="100%">M. Ullio</style></author><author><style face="normal" font="default" size="100%">Andrea Fregosi</style></author><author><style face="normal" font="default" size="100%">Eike Kowallik</style></author><author><style face="normal" font="default" size="100%">Stefano Raffaglio</style></author><author><style face="normal" font="default" size="100%">Andrea Sannino</style></author><author><style face="normal" font="default" size="100%">Marco Milanesio</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">L. Németh</style></author><author><style face="normal" font="default" size="100%">Zied Ben Houidi</style></author><author><style face="normal" font="default" size="100%">G. Dimopoulos</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">L. Baltrunas</style></author><author><style face="normal" font="default" size="100%">Michael Faath</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design of the Reasoner</style></title><short-title><style face="normal" font="default" size="100%">D4.2</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">design</style></keyword><keyword><style  face="normal" font="default" size="100%">private deliverable</style></keyword><keyword><style  face="normal" font="default" size="100%">reasoner</style></keyword><keyword><style  face="normal" font="default" size="100%">WP4</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2014</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D4.2</style></number><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">report</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the Detection of Network Traffic Anomalies in Content Delivery Network Services</style></title><secondary-title><style face="normal" font="default" size="100%">ITC26</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Karlskrona, Sweden</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schiavone, Mirko</style></author><author><style face="normal" font="default" size="100%">Romirer-Maierhofer, Peter</style></author><author><style face="normal" font="default" size="100%">Fiadino, Pierdomenico</style></author><author><style face="normal" font="default" size="100%">Casas, Pedro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Diagnosing Device-Specific Anomalies in Cellular Networks</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2014 CoNEXT on Student Workshop</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">anomaly diagnosis</style></keyword><keyword><style  face="normal" font="default" size="100%">cellular networks.</style></keyword><keyword><style  face="normal" font="default" size="100%">entropy-based analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2680821.2680831</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY, USA</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4503-3282-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P. Casoria</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Jordan Augé</style></author><author><style face="normal" font="default" size="100%">Marc-Oliver Buob</style></author><author><style face="normal" font="default" size="100%">T. Friedman</style></author><author><style face="normal" font="default" size="100%">A. Pescape</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed active measurement of Internet queuing delays</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement (PAM), Extended Abstract</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi14pam-b.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Los Angeles, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Despite growing link capacities, over-dimensioned buffers are still causing, in the Internet of the second decade of the third millenium, hosts to suffer from severe queuing delays (or bufferbloat). While maximum bufferbloat possibly exceeds few seconds, it is far less clear how often this maximum is hit in practice. This paper reports on our ongoing work to build a spatial and temporal map of Internet bufferbloat, describing a system based on distributed agents running on PlanetLab that aims at providing a quantitative answer to the above question.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Bermudez</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio Munafo'</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Distributed Architecture for the Monitoring of Clouds and CDNs: Applications to Amazon AWS</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Network and Service Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amazon</style></keyword><keyword><style  face="normal" font="default" size="100%">AWS</style></keyword><keyword><style  face="normal" font="default" size="100%">CDNs</style></keyword><keyword><style  face="normal" font="default" size="100%">Clouds</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">In press</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Clouds and CDNs are systems that tend to separate the content being requested by users from the physical servers capable of serving it. From the network point of view, monitoring and optimizing performance for the traffic they generate is a challenging task, given the same resource can be located in multiple places, which can in turn change at any time. The first step in understanding Cloud and CDN systems is thus the engineering of a monitoring platform. In this paper, we propose a novel solution which combines passive and active measurements, and whose workflow has been tailored to specifically characterize the traffic generated by Cloud and CDN infrastructures. We validate our platform by performing a longitudinal characterization of the very well known Cloud and CDN infrastructure provider Amazon Web Services (AWS). By observing the traffic generated by more than 50,000 Internet users of an Italian ISP, we explore the EC2, S3 and CloudFront AWS services, unveiling their infrastructure, the pervasiveness of web-services they host, and their traffic allocation policies as seen from our vantage points. Most importantly, we observe their evolution over a two- year long period. The solution provided in this paper can be of interest for i) developers aiming at building measurement tools for Cloud Infrastructure Providers, ii) developers interested in failure and anomaly detection systems, and iii) third-party SLA certificators who can design systems to independently monitor performance. At last, we believe the results about AWS presented in this paper are interesting as they are among the first to unveil properties of AWS as seen from the operator point of view.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Joe Hildebrand</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolving Transport in the Internet</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Internet Computing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span&gt;The Internet’s transport layer has seen little evolution over the past three decades, despite wildly changing requirements. Commonly-deployed transport protocols lack diversity, reducing our ability to evolve them to meet these new application requirements. In this work, the authors describe aspects of this problem and propose a solution space and agenda for improving the situation.&lt;/span&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Eike Kowallik</style></author><author><style face="normal" font="default" size="100%">Stefano Raffaglio</style></author><author><style face="normal" font="default" size="100%">Andrea Fregosi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploiting Hybrid Measurements for Network Troubleshooting</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Networks</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Hybrid measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">WP2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Funchal, PT</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Network measurements are a fundamental pillar to understand network performance and perform root cause analysis in case of problems. Traditionally, either active or passive measurements are considered. While active measurements allow to know exactly the workload injected by the application into the network, the passive measurements can offer a more detailed view of transport and network layer impacts. In this paper, we present a hybrid approach in which active throughput measurements are regularly run while a passive measurement tool monitors the generated packets. This allows us to correlate the application layer measurements obtained by the active tool with the more detailed view offered by the passive monitor.
The proposed methodology has been implemented following the mPlane reference architecture, tools have been installed in the Fastweb network, and we collect measurements for more than three months. We report then a subset of results that show the benefits obtained when correlating active and passive measurements. Among results, we pinpoint cases of congestion, of ADSL misconfiguration, and of modem issues that impair throughput obtained by the users.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">Claudio Testa</style></author><author><style face="normal" font="default" size="100%">Silvio Valenti</style></author><author><style face="normal" font="default" size="100%">Dave Taht</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fighting the bufferbloat: on the coexistence of AQM and low priority congestion control (extended version)</style></title><secondary-title><style face="normal" font="default" size="100%">Elsevier Computer Networks</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi14comnet-b.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">60</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Nowadays, due to excessive queuing, delays on the Internet can grow longer than the round trip time between the Moon and the Earth – for which the ``bufferbloa t'' term was recently coined. Some point to active queue management (AQM) as the solution. Others propose end-to-end low-priority congestion control techniques (LPCC). Under both approaches, promising advances have been made in recent times: notable examples are CoDel for AQM, and LEDBAT for LPCC. In this paper, we warn of a potentially fateful interaction when AQM and LPCC techniques are combined: namely, AQM resets the relative level of priority between best-effort and low-priority congestion control protocols. We validate the generality of our findings by an extended set of experiments with packet-level ns2 simulation, considering 5 AQM techniques and 3 LPCC protocols, and carry on a thorough sensitivity analysis varying several parameters of the networking scenario. We complete the simulation via an experimental campaign conducted on both controlled testbeds and on the Internet, confirming the reprioritization issue to hold in the real world at least under all combination of AQM policies and LPCC protocols available in the Linux kernel. To promote cross-comparison, we make our scripts and dataset available to the research community.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">115--128</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nassopulos, Georges</style></author><author><style face="normal" font="default" size="100%">Rossi, Dario</style></author><author><style face="normal" font="default" size="100%">Gringoli, Francesco</style></author><author><style face="normal" font="default" size="100%">Nava, Lorenzo</style></author><author><style face="normal" font="default" size="100%">Dusi, Maurizio</style></author><author><style face="normal" font="default" size="100%">Santiago del Rio, PedroMaria</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Flow Management at Multi-Gbps: Tradeoffs and Lessons Learned</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-54999-1_1</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><volume><style face="normal" font="default" size="100%">8406</style></volume><pages><style face="normal" font="default" size="100%">1-14</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-54998-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Antonio Lima</style></author><author><style face="normal" font="default" size="100%">Haewoon Kwak</style></author><author><style face="normal" font="default" size="100%">Rade Stanojevic</style></author><author><style face="normal" font="default" size="100%">David Wetherall</style></author><author><style face="normal" font="default" size="100%">Konstantina Papagiannaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From Cells to Streets: Estimating Mobile Paths with Cellular-Side Data</style></title><secondary-title><style face="normal" font="default" size="100%">CoNEXT</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Sydney, Australia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Giuseppe Scavo</style></author><author><style face="normal" font="default" size="100%">Samir Ghamri-Doudane</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gold mining in a River of Internet Content Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">6th International Workshop on Traffic Monitoring and Analysis, TMA</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Content mining</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">URL extraction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">With the advent of Over-The-Top content providers
(OTTs), Internet Service Providers (ISPs) saw their portfolio of
services shrink to the low margin role of data transporters. In
order to counter this effect, some ISPs started to follow big OTTs
like Facebook and Google in trying to turn their data into a
valuable asset. In this paper, we explore the questions of what
meaningful information can be extracted from network data, and
what interesting insights it can provide. To this end, we tackle
the first challenge of detecting “user-URLs”, i.e., those links that
were clicked by users as opposed to those objects automatically
downloaded by browsers and applications. We devise algorithms
to pinpoint such URLs, and validate them on manually collected
ground truth traces. We then apply them on a three-day long
traffic trace spanning more than 19,000 residential users that
generated around 190 million HTTP transactions. We find that
only 1.6% of these observed URLs were actually clicked by users.
As a first application for our methods, we answer the question
of which platforms participate most in promoting the Internet
content. Surprisingly, we find that, despite its notoriety, only 11%
of the user URL visits are coming from Google Search.
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">David Gugelmann</style></author><author><style face="normal" font="default" size="100%">Nevil Brownlee</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Inline Data Integrity Signals for Passive Measurement</style></title><secondary-title><style face="normal" font="default" size="100%">Sixth International Workshop on Traffic Monitoring and Analysis (TMA 2014)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In passive network measurement, the quality of an observed traffic stream is obviously crucial to the quality of the results. Some sources of error (e.g., packet loss at a capture device) are well understood, others less so. In this work, we describe the inline data integrity measurement provided by the QoF TCP-aware flow meter. By instrumenting the data structures QoF uses for detecting lost and retransmitted TCP segments, we can provide an in-band, per-flow estimate of observation loss: segments which were received by the recipient but not observed by the flow meter. We evaluate this mechanism against controlled, induced error, and apply it to two data sets used in previous work.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Lukasz Golab</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-Scale Network Traffic Monitoring with DBStream, a System for Rolling Big Data Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Big Data, IEEE BigData</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Big Data Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Stream Processing</style></keyword><keyword><style  face="normal" font="default" size="100%">network data analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">System Performance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Washington D.C., USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The complexity of the Internet has rapidly increased, making it more important and challenging to design scalable network monitoring tools. Network monitoring typically requires rolling data analysis, i.e., continuously and incrementally updating (rolling-over) various reports and statistics over high-volume data streams. In this paper, we describe DBStream, which is an SQL-based system that explicitly supports incremental queries for rolling data analysis. We also present a performance comparison of DBStream with a parallel data processing engine (Spark), showing that, in some scenarios, a single DBStream node can outperform a cluster of ten Spark nodes on rolling network monitoring workloads. Although our performance evaluation is based on network monitoring data, our results can be generalized to other big data problems with high volume and velocity.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">mPlane: an Intelligent Measurement Plane for the Internet</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Communications Magazine, Special Issue on Monitoring and Troubleshooting Multi-domain Networks using Measurement Federations</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">42</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arianna Rufini</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multilevel Bandwidth Measurements and Capacity Exploitation in Gigabit Passive Optical Networks</style></title><secondary-title><style face="normal" font="default" size="100%">IET Communications</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Fiber Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">GPON</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality of Service</style></keyword><keyword><style  face="normal" font="default" size="100%">TCP</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6980492</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;JOCNAbstract&quot;&gt;&lt;span&gt;We report an experimental investigation on the measurement of the available bandwidth for the users in Gigabit Passive Optical Networks (GPON) and the limitations caused by the Internet protocols, and TCP in particular. We point out that the huge capacity offered by the GPON highlights the enormous differences that can be showed among the available and actually exploitable bandwidth. In fact, while the physical layer capacity can reach value of 100 Mb/s and more, the bandwidth at disposal of the user (i.e. either throughput at transport layer or goodput at application layer) can be much lower when applications and services based on TCP protocol are considered. In the context of Service Level Agreements (SLA) verification, we show how to simultaneously measure throughput and line capacity by offering a method to verify multilayer SLA. We also show how it is possible to better to exploit the physical layer capacity by adopting multiple TCP connections to avoid the bottleneck of a single connection.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">18</style></issue><section><style face="normal" font="default" size="100%">3357</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arianna Rufini</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multilevel QoS vs QoE measurements and Verification of Service Level Agreements</style></title><secondary-title><style face="normal" font="default" size="100%">European Conference on Networks and Communications, EUCNC 2014</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Experimental investigation on QoS measurements in terms of throughput versus access capacity, including a correlation in terms of QoE evaluated for some web TV&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">B. Claise</style></author><author><style face="normal" font="default" size="100%">A. Kobayashi</style></author><author><style face="normal" font="default" size="100%">B. Trammell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Operation of the IP Flow Information Export (IPFIX) Protocol on IPFIX Mediators (RFC 7119)</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ietf.org/rfc/rfc7119.txt</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;pre&gt;This document specifies the operation of the IP Flow Information Export (IPFIX) protocol specific to IPFIX Mediators, including Template and Observation Point management, timing considerations, and other Mediator-specific concerns.&lt;/pre&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">Guilhem Pujol</style></author><author><style face="normal" font="default" size="100%">Xiao Wang</style></author><author><style face="normal" font="default" size="100%">Fabien Mathieu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Peeking Through the BitTorrent Seedbox Hosting Ecosystem</style></title><secondary-title><style face="normal" font="default" size="100%">Traffic Monitoring and Analysis (TMA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi14tma-c.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, we propose a lightweight method for detecting and classifying BitTorrent content providers with a minimal amount of resources. While&lt;br /&gt;heavy methodologies are typically used (which require long term observation&lt;br /&gt;and data exchange with peers of the swarm and/or a semantic analysis of torrent&lt;br /&gt;websites), we instead argue that such complexity can be avoided by analyzing&lt;br /&gt;the correlations between peers and torrents. We apply our methodology to study&lt;br /&gt;over 50K torrents injected in ThePirateBay during one month, collecting more&lt;br /&gt;than 400K IPs addresses. Shortly, we find that exploiting the correlations not&lt;br /&gt;only enhances the classification accuracy keeping the technique lightweight (our&lt;br /&gt;methodology reliably identifies about 150 seedboxes), but also uncovers seeding behaviors that were not previously noticed (e.g., as multi-port and multi-host&lt;br /&gt;seeding). Finally, we correlate the popularity of seedbox hosting in our dataset&lt;br /&gt;to criteria (e.g., cost, storage space, Web popularity) that can bias the selection&lt;br /&gt;process of BitTorrent content providers.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andrea Araldo</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A per-Application Account of Bufferbloat: Causes and Impact on Users</style></title><secondary-title><style face="normal" font="default" size="100%">5th International Workshop on TRaffic Analysis and Characterization (TRAC), Best Paper Award</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/drossi/paper/rossi14trac.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a methodology to gauge the extent of queueing delay (aka bufferbloat) in the Internet, based on purely passive measurement of TCP traffic. We implement our methodology in Tstat and make it available as open source software. We leverage Deep Packet Inspection (DPI) and behavioral classification of Tstat to breakdown the queueing delay across different applications, in order to evaluate the impact of bufferbloat on user experience. We show that there is no correlation between the ISP traffic load and the queueing delay, thus confirming that bufferbloat is related only to the traffic of each single user (or household). Finally, we use frequent itemset mining techniques to associate the amount of queueing delay seen by each host with the set of its active applications, with the goal of investigating the root cause of bufferbloat.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">G.Ellinas</style></author><author><style face="normal" font="default" size="100%">J.Rak</style></author><author><style face="normal" font="default" size="100%">D.Staessens</style></author><author><style face="normal" font="default" size="100%">J.Sterbenz</style></author><author><style face="normal" font="default" size="100%">K.Walkowiak</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Practical issues for the implementation of survivability and recovery techniques in optical networks</style></title><secondary-title><style face="normal" font="default" size="100%">Journal Optical Switching and Networking</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">179</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Practical issues for the implementation of survivability and recovery techniques in optical networks,</style></title><secondary-title><style face="normal" font="default" size="100%">Journal Optical Switching and Networking</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">179</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luca Cittadini</style></author><author><style face="normal" font="default" size="100%">Stefano Vissichio</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the Quality of BGP Route Collectors for iBGP Policy Inference</style></title><secondary-title><style face="normal" font="default" size="100%">IFIP Networking</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bias</style></keyword><keyword><style  face="normal" font="default" size="100%">iBGP policies</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">network topology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A significant portion of what is known about Internet routing stems out from&amp;nbsp;public BGP datasets. For this reason, numerous research efforts were devoted to&amp;nbsp;(&lt;em&gt;i&lt;/em&gt;) assessing the (in)completeness of the datasets, (&lt;em&gt;ii&lt;/em&gt;) identifying biases&amp;nbsp;in the dataset, and (&lt;em&gt;iii&lt;/em&gt;) augmenting data quality by optimally placing new&amp;nbsp;collectors. However, those studies focused on techniques to extract information&amp;nbsp;about the AS-level Internet topology.&lt;/p&gt;&lt;p&gt;In this paper, we show that considering different metrics influences the&amp;nbsp;conclusions about biases and collector placement. Namely, we compare AS-level&amp;nbsp;topology discovery with \iac inference. We find that the same datasets exhibit&amp;nbsp;significantly diverse biases for these two metrics. For example, the sensitivity&amp;nbsp;to the number and position of collectors is noticeably different. Moreover, for&amp;nbsp;both metrics, the marginal utility of adding a new collector is strongly&amp;nbsp;localized with respect to the proximity of the collector. Our results suggest&amp;nbsp;that the ``optimal'' position for new collectors can only be defined with&amp;nbsp;respect to a specific metric, hence posing a fundamental trade-off for&amp;nbsp;maximizing the utility of extensions to the BGP data collection infrastructure.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Vincenzo Attanasio</style></author><author><style face="normal" font="default" size="100%">Donato Del Buono</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quality of Service Management based on Software Defined Networking Approach in wide GbE Networks</style></title><secondary-title><style face="normal" font="default" size="100%">Euromed</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">GbE</style></keyword><keyword><style  face="normal" font="default" size="100%">PON</style></keyword><keyword><style  face="normal" font="default" size="100%">QoS</style></keyword><keyword><style  face="normal" font="default" size="100%">SDN</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;strong&gt;This work experimentally demonstrates how to control and manage user Quality of Service (QoS) by acting on the switching on-off of the optical Gigabit Ethernet (GbE) interfaces in a wide area network test bed including routers and GPON accesses. The QoS is monitored at the user location by means of active probes developed in the framework of the FP7 MPLANE project. The network topology is managed according to some current Software Defined Network issues and in particular an Orchestrator checks the user quality, the traffic load in the GbE links and manages the network interface reconfiguration when congestion occurs in some network segments.&lt;/strong&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Roberto Bifulco</style></author><author><style face="normal" font="default" size="100%">Francesco Gringoli</style></author><author><style face="normal" font="default" size="100%">Fabian Schneider</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reactive Logic in Software-Defined Networking: Measuring Flow-Table Requirements</style></title><secondary-title><style face="normal" font="default" size="100%">5th International Workshop on TRaffic Analysis and Characterization (TRAC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Nicosia, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">B. Trammell</style></author><author><style face="normal" font="default" size="100%">P. Aitken</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Revision of the tcpControlBits IP Flow Information Export (IPFIX) Information Element (RFC 7125)</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ietf.org/rfc/rfc7125.txt</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;pre&gt;This document revises the tcpControlBits IP Flow Information Export (IPFIX) Information Element as originally defined in &lt;a href=&quot;http://tools.ietf.org/html/rfc5102&quot;&gt;RFC 5102&lt;/a&gt; to reflect changes to the TCP Flags header field since &lt;a href=&quot;http://tools.ietf.org/html/rfc793&quot;&gt;RFC 793&lt;/a&gt;.&lt;/pre&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Revisiting size-based scheduling with estimated job sizes</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dell'Amico, Matteo</style></author><author><style face="normal" font="default" size="100%">Carra, Damiano</style></author><author><style face="normal" font="default" size="100%">Pastorelli, Mario</style></author><author><style face="normal" font="default" size="100%">Michiardi, Pietro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Revisiting size-based scheduling with estimated job sizes</style></title><secondary-title><style face="normal" font="default" size="100%">{MASCOTS} 2014, {IEEE} 22nd {I}nternational {S}ymposium on {M}odeling analysis and simulation of computer and telecommunication systems, {S}eptember 9-11, 2014, {P}aris, {F}rance / {A}lso published on {A}r{X}iv</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.eurecom.fr/publication/4268</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">{P}aris, {FRANCE}</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. Colabrese</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Scalable accurate consolidation of passively measured statistical data</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement (PAM), Extended Abstract</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://perso.telecom-paristech.fr/~drossi/paper/rossi14pam-a.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Los Angeles, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Passive probes continuously collect a significant amount of traffic vol- ume, and autonomously generate statistics on a large number of metrics. A common statistical output of passive probe is represented by probability mass functions (pmf). The need for consolidation of several pmfs arises in two contexts, namely: (i) whenever a central point collects and aggregates measurement of multiple disjoint vantage points, and (ii) whenever a local measurement processed at a single vantage point needs to be distributed over multiple cores of the same physical probe, in order to cope with growing link capacity. Taking an experimental approach, we study both cases assessing the impact of different consolidation strategies, obtaining general design and tuning guidelines.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Ram Keralapura</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SeLeCT: Self-Learning Classifier for Internet Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Network and Service Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">self-seeding</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">unsupervised machine learning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Network visibility is a critical part of traffic engineering, network management, and security. The most popular&amp;nbsp;current solutions - Deep Packet Inspection (DPI) and statistical&amp;nbsp;classification, deeply rely on the availability of a training set.&amp;nbsp;Besides the cumbersome need to regularly update the signatures,&amp;nbsp;their visibility is limited to classes the classifier has been trained&amp;nbsp;for. Unsupervised algorithms have been envisioned as a viable&amp;nbsp;alternative to automatically identify classes of traffic. However,&amp;nbsp;the accuracy achieved so far does not allow to use them for traffic&amp;nbsp;classification in practical scenario.&lt;/p&gt;&lt;p&gt;To address the above issues, we propose SeLeCT, a Self-Learning Classifier for Internet Traffic. It uses unsupervised algorithms along with an adaptive seeding approach to automatically&amp;nbsp;let classes of traffic emerge, being identified and labeled. Unlike&amp;nbsp;traditional classifiers, it requires neither a-priori knowledge of&amp;nbsp;signatures nor a training set to extract the signatures. Instead,&amp;nbsp;SeLeCT automatically groups flows into pure (or homogeneous)&amp;nbsp;clusters using simple statistical features. SeLeCT simplifies label&amp;nbsp;assignment (which is still based on some manual intervention) so&amp;nbsp;that proper class labels can be easily discovered. Furthermore,&amp;nbsp;SeLeCT uses an iterative seeding approach to boost its ability to&amp;nbsp;cope with new protocols and applications.&lt;/p&gt;&lt;p&gt;We evaluate the performance of SeLeCT using traffic traces&amp;nbsp;collected in different years from various ISPs located in 3&amp;nbsp;different continents. Our experiments show that SeLeCT achieves&amp;nbsp;excellent precision and recall, with overall accuracy close to 98%.&amp;nbsp;Unlike state-of-art classifiers, the biggest advantage of SeLeCT&amp;nbsp;is its ability to discover new protocols and applications in an&amp;nbsp;almost automated fashion.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">144</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Understanding HTTP Traffic and CDN Behavior from the Eyes of a Mobile ISP</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurements Conference (PAM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">R. Mazloum</style></author><author><style face="normal" font="default" size="100%">M.-O. Buob</style></author><author><style face="normal" font="default" size="100%">J. Auge</style></author><author><style face="normal" font="default" size="100%">B. Baynat</style></author><author><style face="normal" font="default" size="100%">T. Friedman</style></author><author><style face="normal" font="default" size="100%">D. Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Violation of Interdomain Routing Assumptions</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement (PAM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/~drossi/paper/rossi14pam-c.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Los Angeles, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Mirko Schiavone</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vivisecting WhatsApp through Large-Scale Measurements in Mobile Networks</style></title><secondary-title><style face="normal" font="default" size="100%">SIGCOMM 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Large-Scale Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">mobile networks</style></keyword><keyword><style  face="normal" font="default" size="100%">WhatsApp</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Chicago, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;WhatsApp, the new giant in instant multimedia messaging in mobile networks is rapidly increasing its popularity, taking over the traditional SMS/MMS messaging. In this paper we present the first large-scale characterization of WhatsApp, useful among others to ISPs willing to understand the impacts of this and similar applications on their networks. Through the combined analysis of passive measurements at the core of a national mobile network, worldwide geo-distributed active measurements, and traffic analysis at end devices, we show that: (i) the WhatsApp hosting architecture is highly centralized and exclusively located in the US; (ii) video sharing covers almost 40% of the total WhatsApp traffic volume; (iii) flow characteristics depend on the OS of the end device; (iv) despite the big latencies to US servers, download throughputs are as high as 1.5 Mbps; (v) users react immediately and negatively to service outages through social networks feedbacks.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Casas, Pedro</style></author><author><style face="normal" font="default" size="100%">D'Alconzo, Alessandro</style></author><author><style face="normal" font="default" size="100%">Fiadino, Pierdomenico</style></author><author><style face="normal" font="default" size="100%">Bär, Arian</style></author><author><style face="normal" font="default" size="100%">Finamore, Alessandro</style></author><author><style face="normal" font="default" size="100%">Zseby, Tanja</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">When YouTube Does not Work - Analysis of QoE-Relevant Degradation in Google CDN Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">Network and Service Management, IEEE Transactions on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CDN distributed services</style></keyword><keyword><style  face="normal" font="default" size="100%">CDN server selection strategies</style></keyword><keyword><style  face="normal" font="default" size="100%">client-server systems</style></keyword><keyword><style  face="normal" font="default" size="100%">content delivery network</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Degradation</style></keyword><keyword><style  face="normal" font="default" size="100%">dynamic approach</style></keyword><keyword><style  face="normal" font="default" size="100%">dynamic server selection strategies</style></keyword><keyword><style  face="normal" font="default" size="100%">end-user QoE</style></keyword><keyword><style  face="normal" font="default" size="100%">end-user quality of experience</style></keyword><keyword><style  face="normal" font="default" size="100%">European ISP</style></keyword><keyword><style  face="normal" font="default" size="100%">Google</style></keyword><keyword><style  face="normal" font="default" size="100%">Google CDN traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">Google server selection strategies</style></keyword><keyword><style  face="normal" font="default" size="100%">IP networks</style></keyword><keyword><style  face="normal" font="default" size="100%">iterative structured process</style></keyword><keyword><style  face="normal" font="default" size="100%">load reduction</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE-relevant anomaly characterization</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE-relevant anomaly detection</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE-relevant anomaly diagnosis</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE-relevant degradation</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality of Experience</style></keyword><keyword><style  face="normal" font="default" size="100%">Servers</style></keyword><keyword><style  face="normal" font="default" size="100%">social networking (online)</style></keyword><keyword><style  face="normal" font="default" size="100%">statistical analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">statistical analysis methodologies</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical Data Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">telecommunication traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Videos</style></keyword><keyword><style  face="normal" font="default" size="100%">watching experience improvement</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube flow trace collection</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube QoE-relevant degradation</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube videos</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">441-457</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Who to Blame when YouTube is not Working? Detecting Anomalies in CDN Provisioned Services</style></title><secondary-title><style face="normal" font="default" size="100%">TRAC</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Nicosia, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YouTube All Around: Characterizing YouTube from Mobile and Fixed-line Network Vantage Points</style></title><secondary-title><style face="normal" font="default" size="100%">EuCNC</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2014</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Bologna, IT</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Andreas Sackl</style></author><author><style face="normal" font="default" size="100%">Alessandro D'Alconzo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YouTube in the Move: Understanding the Performance of YouTube in Cellular Networks (BEST PAPER AWARD RUNNER UP)</style></title><secondary-title><style face="normal" font="default" size="100%">Wireless Days 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cellular Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">End-device Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Rio de Janeiro, Brazil</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;YouTube is the most popular and volume-dominant service in today's Internet, and is changing the way ISPs manage their networks. Understanding the performance of YouTube traffic is paramount for ISPs, specially for mobile operators, who must handle the huge surge of traffic with the constraints and challenges of cellular networks. In this paper we present an empirical analysis of the performance of YouTube flows accessed through a national-wide cellular network, considering download throughput as well as end-user Quality of Experience (QoE) metrics. The analysis considers the characteristics and impacts of the Content Delivery Network hosting YouTube, and compares its behavior with other popular HTTP video streaming services accessed through cellular networks. The QoE analysis is performed through end-user device measurements, which directly reflect the experience of the end-users. Our study additionally shows the potentiality of monitoring YouTube performance in cellular networks directly from the smart-phones of the users, bypassing the traffic visibility loss at the core of the network introduced by traffic encryption (e.g., HTTPS).&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pietro Michiardi</style></author><author><style face="normal" font="default" size="100%">Antonio Barbuzzi</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Daniele Apiletti</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Tania Cerquitelli</style></author><author><style face="normal" font="default" size="100%">Silvia Chiusano</style></author><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author><author><style face="normal" font="default" size="100%">A. Rufini</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">A. Valentii</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">L. Németh</style></author><author><style face="normal" font="default" size="100%">R. Szalay</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D’Alconzo</style></author><author><style face="normal" font="default" size="100%">A Bär</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">YiXi Gong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Basic Network Data Analysis</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">storage</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D3.1</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This document describes the requirements, input, output for the algorithms needed to perform analytic tasks on a large amount of data, in the context of WP3. Starting from the use cases defined in WP1, we identify the algorithms needed to address the various scenario requirements. Operating on a large amount of data, these algorithms strive for parallel and scalable approaches; the designing and implementation of the algorithm itself can be a challenging research task since today very little is known concerning how to develop efficient and scalable algorithms that runs on parallel processing frameworks.&lt;br /&gt;The algorithm in the storage layer are characterized by the fact that they operate on a large amount of data, and produce a concise representation of it, extracting features and aggregating it, so that the produced output is easier to handle and understand. Depending on the amount of data produced, on the scenario characteristics and on the time constraints, algorithms can require a real time (or near real time) or a batch processing.&lt;br /&gt;For each algorithm and use case, the input data and the initial state, the computation to run and the output produced are described.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Herman Slatman</style></author><author><style face="normal" font="default" size="100%">Aiko Pras</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Benchmarking Personal Cloud Storage</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference - IMC</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Active Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Personal Cloud Storage</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.simpleweb.org/wiki/Cloud_benchmarks</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Barcelona (ES)</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Personal cloud storage services are data-intensive applica- tions already producing a significant share of Internet traffic. Several solutions offered by different companies attract more and more people. However, little is known about each service capabilities, architecture and – most of all – performance implications of design choices. This paper presents a methodology to study cloud storage services. We apply our methodology to compare 5 popular offers, revealing different system architectures and capabilities. The implications on performance of different designs are assessed executing a series of benchmarks. Our results show no clear winner, with all services suffering from some limitations or having potential for improvement. In some scenarios, the upload of the same file set can take seven times more, wasting twice as much capacity. Our methodology and results are useful thus as both benchmark and guideline for system design.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">C. Testa</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">A. Rao</style></author><author><style face="normal" font="default" size="100%">A. Legout</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data Plane Throughput vs Control Plane Delay: Experimental Study of BitTorrent Performance</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE P2P'XIII</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13p2p-a.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we address the trade-off between the data plane efficiency and the control plane timeliness for the BitTorrent performance. We argue that loss-based congestion control protocols can fill large buffers, leading to a higher end-to-end delay, unlike low-priority or delay-based congestion control protocols. We perform experiments for both the uTorrent and mainline BitTorrent clients, and we study the impact of uTP (a novel transport protocol proposed by BitTorrent) and several TCP congestion control algorithms (Cubic, New Reno, LP, Vegas and Nice) on the download completion time. Briefly, in case peers in the swarm all use the same congestion control algorithm, we observe that the specific algorithm has only a limited impact on the swarm performance. Conversely, when a mix of TCP congestion control algorithms coexists, peers employing a delay-based low-priority algorithm exhibit shorter completion time.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A Bär</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D’Alconzo</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Antonio Barbuzzi</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Gianni De Rosa</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Jordan Augé</style></author><author><style face="normal" font="default" size="100%">Marc-Oliver Buob</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Database Layer Design</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">databases</style></keyword><keyword><style  face="normal" font="default" size="100%">repositories</style></keyword><keyword><style  face="normal" font="default" size="100%">storage</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D3.2</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Samir Ghamri-Doudane</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">M. Milanesio</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">Alessandro D’Alconzo</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">L. Máthé</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">L. Baltrunas</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author><author><style face="normal" font="default" size="100%">Guy Leduc</style></author><author><style face="normal" font="default" size="100%">Y. Liao</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design of Analysis Modules</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D4.1</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><isbn><style face="normal" font="default" size="100%">D4.1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Araldo</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Dissecting Bufferbloat: Measurement and Per-Application Breakdown of Queueing Delay</style></title><secondary-title><style face="normal" font="default" size="100%">ACM CoNEXT'13, Student Workshop</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13conext.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a passive methodology to estimate the queueing delay incurred by TCP traffic, and additionally leverage DPI classification to breakdown the delay across different applications. Ultimately, we correlate the queueing delay to the performance perceived by the users of that applications, depending on their delay-sensitivity. We implement our methodology in Tstat, and make it available 1 as open source software to the community. We validate and tune the tool, and run a preliminary measurement campaign based on a real ISP traffic trace, showing interesting yet partly counter-intuitive results.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yongjun Liao</style></author><author><style face="normal" font="default" size="100%">Wei Du</style></author><author><style face="normal" font="default" size="100%">Pierre Geurts</style></author><author><style face="normal" font="default" size="100%">Guy Leduc</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DMFSGD: A decentralized matrix factorization algorithm for network distance prediction</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE/ACM Transactions on Networking</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">matrix completion</style></keyword><keyword><style  face="normal" font="default" size="100%">matrix factorization</style></keyword><keyword><style  face="normal" font="default" size="100%">network distance prediction</style></keyword><keyword><style  face="normal" font="default" size="100%">stochastic gradient descent</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The knowledge of end-to-end network distances is&amp;nbsp;essential to many Internet applications. As active probing of all&amp;nbsp;pairwise distances is infeasible in large-scale networks, a natural&amp;nbsp;idea is to measure a few pairs and to predict the other ones&amp;nbsp;without actually measuring them. This paper formulates the&amp;nbsp;prediction problem as matrix completion where the unknown&amp;nbsp;entries in a pairwise distance matrix constructed from a network&amp;nbsp;are to be predicted. By assuming that the distance matrix has&amp;nbsp;a low-rank characteristics, the problem is solvable by lowrank&amp;nbsp;approximation based on matrix factorization. The new&amp;nbsp;formulation circumvents the well-known drawbacks of existing&amp;nbsp;approaches based on Euclidean embedding.&lt;/p&gt;&lt;p&gt;A new algorithm, so-called Decentralized Matrix Factorization&amp;nbsp;by Stochastic Gradient Descent (DMFSGD), is proposed. By&amp;nbsp;letting network nodes exchange messages with each other, the&amp;nbsp;algorithm is fully decentralized and only requires each node&amp;nbsp;to collect and to process local measurements, with neither&amp;nbsp;explicit matrix constructions nor special nodes such as landmarks&amp;nbsp;and central servers. In addition, we compared comprehensively&amp;nbsp;matrix factorization and Euclidean embedding to demonstrate&amp;nbsp;the suitability of the former on network distance prediction. We&amp;nbsp;further studied the incorporation of a robust loss function and&amp;nbsp;of non-negativity constraints. Extensive experiments on various&amp;nbsp;publicly-available datasets of network delays show not only the&amp;nbsp;scalability and the accuracy of our approach, but also its usability&amp;nbsp;in real Internet applications.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><section><style face="normal" font="default" size="100%">1511</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Nicolas Bermudez</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio M Munafo'</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploring the Cloud from Passive Measurements: the Amazon AWS case</style></title><secondary-title><style face="normal" font="default" size="100%">The 32nd Annual IEEE International Conference on Computer Communications (INFOCOM'2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><pub-location><style face="normal" font="default" size="100%">Turin, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cloud Providers are nowadays the most popular way to quickly deploy new services on the Internet. Understanding mechanisms currently adopted in cloud design is fundamental to identify possible bottlenecks, to optimize performance, and to design more efficient platforms. This paper presents a characterization of Amazon's Web Services (AWS), the most prominent cloud provider that offers computing, storage, and content delivery platforms. Leveraging passive measurements collected from several vantage points in Italy for several months, we explore the EC2, S3 and CloudFront AWS services to unveil their infrastructure, the pervasiveness of content they host, and their traffic allocation policies. Measurements reveal that most of the content residing on EC2 and S3 is served by one single Amazon datacenter located in Virginia despite it appears to be the worst performing one for Italian users. This causes traffic to take long and expensive paths in the network. Since no automatic migration and load-balancing policies are offered by AWS among different locations, content is exposed to outages, as we were able to observe in our data. The CloudFront CDN, on the contrary, shows much better performance thanks to the effective cache selection policy that serves 98% of the traffic from the nearest available cache. CloudFront exhibits also dynamic load-balancing policies, in contrast to the static allocation of instances on EC2 and S3. Information presented in this paper will be useful for developers aiming at entrusting AWS to deploy their contents, and for researchers willing to improve cloud design.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">C. Testa</style></author><author><style face="normal" font="default" size="100%">S. Valenti</style></author><author><style face="normal" font="default" size="100%">D. Taht</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fighting the bufferbloat: on the coexistence of AQM and low priority congestion control</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE INFOCOM Workshop on Traffic Monitoring and Analysis  (TMA'13)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bufferbloat</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13tma-b.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alessandro Capello</style></author><author><style face="normal" font="default" size="100%">Fabrizio Invernizzi</style></author><author><style face="normal" font="default" size="100%">Omar Jabr</style></author><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Marco Milanesio</style></author><author><style face="normal" font="default" size="100%">Ernst Biersack</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Arianna Rufini</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">First Data Collection Track Record</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data sets</style></keyword><keyword><style  face="normal" font="default" size="100%">integration</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement systems</style></keyword><keyword><style  face="normal" font="default" size="100%">scenarios</style></keyword><keyword><style  face="normal" font="default" size="100%">use cases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D5.1</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Private Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pastorelli Mario</style></author><author><style face="normal" font="default" size="100%">Barbuzzi Antonio</style></author><author><style face="normal" font="default" size="100%">Carra Damiano</style></author><author><style face="normal" font="default" size="100%">Dell'Amico Matteo</style></author><author><style face="normal" font="default" size="100%">Michiardi Pietro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HFSP: Size-based Scheduling for Hadoop</style></title><secondary-title><style face="normal" font="default" size="100%">BIGDATA 2013, IEEE International Conference on BigData, October 6-9, 2013, Santa-Clara, CA, USA</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.eurecom.fr/publication/4106</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">A Bär</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HTTPTag: A Flexible On-line HTTP Classification System for Operational 3G Networks</style></title><secondary-title><style face="normal" font="default" size="100%">INFOCOM'2013 Demo/Poster Session (INFOCOM'2013 - Demo/Poster Session)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">3G Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP</style></keyword><keyword><style  face="normal" font="default" size="100%">Pattern Matching</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Classification</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><pub-location><style face="normal" font="default" size="100%">Turin, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The popularity of web-based services and applications like YouTube and Facebook has taken HTTP back to the pole position on end-user traffic consumption. We present HTTPTag, a flexible on-line HTTP classification system based on pattern matching and tagging. HTTPTag recognizes on the fly and tracks the evolution of more than 280 applications running on top of HTTP in an operational 3G network, representing more than 70\% of the total HTTP traffic volume consumed by its customers. HTTPTag improves the network traffic visibility of an operator, performing tasks such as top-services ranking, long-term monitoring of applications popularity, and trend analysis among others.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Y. Nicolas</style></author><author><style face="normal" font="default" size="100%">D. Wolff</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">I tube, YouTube, P2PTube: assessing ISP benefits of peer-assisted caching of YouTube content</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE P2P'XIII</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13p2p-b.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper proposes P2PTube, a very simple yet effective set-top-box system to assist diffusion of YouTube videos. We argue that, due to the spatial and temporal nature of video requests, the simplest design already provides non marginal gains. Our trace driven evaluation shows that, with moderate cache size (100MB) and nominal upload rates (500Kbps), about half of the video requests could be served by P2PTube. Interestingly, we also see that non marginal gains are already achievable with tiny caches – which is tied to the presence of advertisement prior that the actual video requested by the user.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IP Mining: Extracting Knowledge from the Dynamics of the Internet Addressing Space (BEST PAPER AWARD)</style></title><secondary-title><style face="normal" font="default" size="100%">25th International Teletraffic Congress, ITC 25</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">IP Addressing Space</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Classification and Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Going back to the Internet of one decade ago, HTTP-based content and web services were provided by centralized or barely distributed servers. Single hosts providing exclusive services at fixed IP addresses was the standard approach. Current situation has drastically changed, and the mapping of IPs to different content and services is nowadays extremely dynamic. The adoption of large CDNs by major Internet players, the extended usage of transparent content caching, the explosion of Cloud-based services, and the decoupling between content providers and the hosting infrastructure have created a difficult to manage Internet landscape. Understanding such a complex scenario is paramount for network operators, both to control the traffic on their networks and to improve the quality experienced by their customers, specially when something goes wrong. Using a full week of HTTP traffic traces collected at the mobile broadband network of a major European ISP, this paper studies the associations between web services, the hosting organizations-ASes, and the content servers' IPs. By mining correlations among these, we extract useful insights about the dynamics of the IP addressing space used by the top web services, and the way content providers and hosting organizations deliver their services to the mobile endusers. The extracted knowledge is applied on two specific use-cases, the former on hosting and service delivery characterization, the latter on automatic IP-based HTTP services classification.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">D. Papadimitriou</style></author><author><style face="normal" font="default" size="100%">L. Fàbrega</style></author><author><style face="normal" font="default" size="100%">P. Vilà</style></author><author><style face="normal" font="default" size="100%">D. Careglio</style></author><author><style face="normal" font="default" size="100%">P. Demeester</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measurement-based Experimental Research Methodology</style></title><secondary-title><style face="normal" font="default" size="100%">Measurement Methodology and Tools</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science Series</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><volume><style face="normal" font="default" size="100%">7586</style></volume><pages><style face="normal" font="default" size="100%">pp 5-22</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Measurement-Centered Approach to Latency Reduction</style></title><secondary-title><style face="normal" font="default" size="100%">ISOC Workshop on Reducing Internet Latency</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.internetsociety.org/latency2013</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">London, England</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Position Paper</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mini-IPC: A Minimalist Approach for HTTP Traffic Classification using IP Addresses</style></title><secondary-title><style face="normal" font="default" size="100%">4th International Workshop on Traffic Analysis and Classification, TRAC 2013</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CDNs</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">IP Addressing Space</style></keyword><keyword><style  face="normal" font="default" size="100%">Mobile Networks' Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Classification and Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The popularity of web-based services and multimedia applications like YouTube, Google Web Search, Facebook, and a bewildering range of Internet applications has taken HTTP back to the pole position on end-user traffic consumption. Today’s Internet users exchange most of their content via HTTP. In this paper we address the problem of on-line HTTP traffic classification from network measurements. Building on the results provided by HTTPTag, a flexible system for on-line HTTP classification, we present and explore Mini-IPC. Mini-IPC is a minimalist approach for classifying HTTP flows using only the IP addresses of the servers hosting the corresponding content. Using one full week of HTTP traffic traces collected at the mobile broadband network of a major European ISP, we investigate to which extent the most popular HTTP-based services are hosted by well-defined sets of IP addresses, and evaluate the performance of Mini-IPC to classify these services using IPs only.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Emilio Leonardi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling the interdependency of low-priority congestion control and active queue management</style></title><secondary-title><style face="normal" font="default" size="100%"> 25th International Teletraffic Congress (ITC'25), Runner up for best-paper award</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recently, a negative interplay has been shown to&lt;br /&gt;arise when scheduling/AQM techniques and low-priority conges-&lt;br /&gt;tion control protocols are used together: namely, AQM resets&lt;br /&gt;the relative level of priority among congestion control protocols.&lt;br /&gt;This work explores this issue by (i) studying a fluid model that&lt;br /&gt;describes system dynamics of heterogeneous congestion control&lt;br /&gt;protocols competing on a bottleneck link governed by AQM and&lt;br /&gt;(ii) proposing a system level solution able to reinstate priorities&lt;br /&gt;among protocols.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author><author><style face="normal" font="default" size="100%">Fabrizio Invernizzi</style></author><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">mPlane Architecture Speciﬁcation</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">architecture</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">platform</style></keyword><keyword><style  face="normal" font="default" size="100%">scenario</style></keyword><keyword><style  face="normal" font="default" size="100%">use case</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D1.3</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multi-agent Statistical Relational Learning</style></title><secondary-title><style face="normal" font="default" size="100%">2nd European Teletraffic Seminar (ETS 2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Walter Bellante</style></author><author><style face="normal" font="default" size="100%">Rosa Vilardi</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On Netflix catalog dynamics and caching performance</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE CAMAD</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13camad.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Multimedia streaming applications have substantially changed the market policy of an increasing number of content providers that offer streaming services to the users. The need for effective video content delivery re-fueled interest for caching: since the Web-like workload of the 90s are not longer fit to describe the new Web of videos, in this work we investigate the suitability of the publicly available Netflix dataset for caching studies. Our analysis shows that, as the dataset continuously evolves (i) a steady state description is not statistically meaningful and (ii) despite the cache hit ratio decreases due to the growth of active movies in the catalog, simple caching replacement approaches are close to the optimum given the growing skew in the popularity distribution over the time. Additionally, we point out that, since the dataset reports logs of movie ratings, anomalies arise when ratings are considered to be movie views. At the same time, we show anomalies yield conservative caching results, that reinforces the soundness of our study.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yves Vanaubel</style></author><author><style face="normal" font="default" size="100%">Jean-Jacques Pansiot</style></author><author><style face="normal" font="default" size="100%">Pascal Mérindol</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Network Fingerprinting: TTL-Based Router Signature</style></title><secondary-title><style face="normal" font="default" size="100%">ACM/USENIX Internet Measurement Conference (IMC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">fingerprinting</style></keyword><keyword><style  face="normal" font="default" size="100%">initial TTL</style></keyword><keyword><style  face="normal" font="default" size="100%">MPLS router signature</style></keyword><keyword><style  face="normal" font="default" size="100%">network discovery</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Barcelona, Spain</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Fingerprinting networking equipment has many potential applications and benefits&amp;nbsp;in network management and security. More generally, it is useful for the&amp;nbsp;understanding of network structures and their behaviors. In this paper, we&amp;nbsp;describe a simple fingerprinting mechanism based on the initial TTL values used&amp;nbsp;by routers to reply to various probing messages. We show that main classes&lt;br /&gt;obtained using this simple mechanism are meaningful to distinguish routers&amp;nbsp;platforms. Besides, it comes at a very low additional cost compared to standard&amp;nbsp;active topology discovery measurements. As a proof of concept, we apply our&amp;nbsp;method to gain more insight on the behavior of MPLS routers and to, thus, more&amp;nbsp;accurately quantify their visible/invisible deployment.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yves Vanaubel</style></author><author><style face="normal" font="default" size="100%">Jean-Jacques Pansiot</style></author><author><style face="normal" font="default" size="100%">Pascal Mérindol</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Network Fingerprinting: TTL-Based Router Signatures</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Internet Measurement Conference (IMC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">fingerprinting</style></keyword><keyword><style  face="normal" font="default" size="100%">initial TTL</style></keyword><keyword><style  face="normal" font="default" size="100%">MPLS</style></keyword><keyword><style  face="normal" font="default" size="100%">network discovery</style></keyword><keyword><style  face="normal" font="default" size="100%">router signatures</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Barcelona, Spain</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Fingerprinting networking equipment has many potential applications and benefits&amp;nbsp;in network management and security. More generally, it is useful for the&amp;nbsp;understanding of network structures and their behaviors. In this paper, we&amp;nbsp;describe a simple fingerprinting mechanism based on the initial TTL values used&amp;nbsp;by routers to reply to various probing messages. We show that main classes&amp;nbsp;obtained using this simple mechanism are meaningful to distinguish routers&lt;br /&gt;platforms. Besides, it comes at a very low additional cost compared to standard&amp;nbsp;active topology discovery measurements. As a proof of concept, we apply our&amp;nbsp;method to gain more insight on the behavior of MPLS routers and to, thus, more&amp;nbsp;accurately quantify their visible/invisible deployment.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">C. Chirichella</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">C. Testa</style></author><author><style face="normal" font="default" size="100%">T. Friedman</style></author><author><style face="normal" font="default" size="100%">A. Pescape</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Passive bufferbloat measurement exploiting transport layer information</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE GLOBECOM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13globecom.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Saverio Niccolini</style></author><author><style face="normal" font="default" size="100%">Antonio Barbuzzi</style></author><author><style face="normal" font="default" size="100%">M. Milanesio</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Edion Tego</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Andrea Fregosi</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author><author><style face="normal" font="default" size="100%">Fabrizio Invernizzi</style></author><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Plans for Using and Disseminating mPlane Knowledge</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">dissemination</style></keyword><keyword><style  face="normal" font="default" size="100%">exploitation</style></keyword><keyword><style  face="normal" font="default" size="100%">open-source software</style></keyword><keyword><style  face="normal" font="default" size="100%">publications</style></keyword><keyword><style  face="normal" font="default" size="100%">standardization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D7.2</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>9</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">python-ipfix-0.9.1</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://pypi.python.org/pypi/ipfix</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 5&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;This module provides a Python interface to IPFIX message streams, and provides tools for building IPFIX Exporting and Collecting Processes. It handles message framing and deframing, encoding and decoding IPFIX data records using templates, and a bridge between IPFIX ADTs and appropriate Python data types.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mayutan Arumaithurai</style></author><author><style face="normal" font="default" size="100%">Jan Seedorf</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Edo Monticelli</style></author><author><style face="normal" font="default" size="100%">Renato Lo Cigno</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quality-of-Experience driven Acceleration of Thin Client Connections</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Symposium on Network Computing and Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2013</style></date></pub-dates></dates><edition><style face="normal" font="default" size="100%">12</style></edition><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">C. Chirichella</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">C. Testa</style></author><author><style face="normal" font="default" size="100%">T. Friedman</style></author><author><style face="normal" font="default" size="100%">A. Pescape</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Remotely Gauging Upstream Bufferbloat Delays</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement (PAM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/ drossi/paper/rossi13pam.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">  ``Bufferbloat'' is the growth in buffer size that has led Internet
  delays to occasionally exceed the light propagation delay from the Earth
  to the Moon. Manufacturers have built in large buffers to prevent
  losses on Wi-Fi, cable and ADSL links. But the combination of some links'
  limited bandwidth with TCP's tendency to saturate that
  bandwidth results in  excessive queuing delays. In response, new
  congestion control protocols such as BitTorrent's uTP/LEDBAT aim at
  explicitly limiting the delay that they add over the bottleneck link.
This work proposes and validate a methodology to monitor the upstream
    queuing delay experienced by remote hosts, both those using
  LEDBAT, through LEDBAT's native one-way delay measurements, and
  those using TCP (via the Time-stamp Option). 
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gregory Detal</style></author><author><style face="normal" font="default" size="100%">Benjamin Hesmans</style></author><author><style face="normal" font="default" size="100%">Olivier Bonaventure</style></author><author><style face="normal" font="default" size="100%">Yves Vanaubel</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Revealing Middlebox Interference with Tracebox</style></title><secondary-title><style face="normal" font="default" size="100%">ACM/USENIX Internet Measurement Conference (IMC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">middlebox</style></keyword><keyword><style  face="normal" font="default" size="100%">network discovery</style></keyword><keyword><style  face="normal" font="default" size="100%">tracebox</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Middleboxes such as firewalls, NAT, proxies, or Deep Pack-et Inspection play an&amp;nbsp;increasingly important role in various types of IP networks, including&amp;nbsp;enterprise and cellular networks. Recent studies have shed the light on their&amp;nbsp;impact on real traffic and the complexity of managing them. Network operators&amp;nbsp;and researchers have few tools to understand the impact of those boxes on any&lt;br /&gt;path. In this paper, we propose tracebox, an extension to the widely used&amp;nbsp;traceroute tool, that is capable of detecting various types of middlebox&amp;nbsp;interference over almost any path. &amp;nbsp;tracebox sends IP packets containing TCP&amp;nbsp;segments with different TTL values and analyses the packet encapsulated in the&amp;nbsp;returned ICMP messages. Further, as recent routers quote, in the ICMP message,&amp;nbsp;the entire IP packet that they received, tracebox is able to detect any&amp;nbsp;modification performed by upstream middleboxes. In addition, tracebox can often&amp;nbsp;pinpoint the network hop where the middlebox interference occurs. We evaluate&amp;nbsp;tracebox with measurements performed on PlanetLab nodes. Our analysis reveals&amp;nbsp;various types of middleboxes that were not expected on such an experimental&amp;nbsp;testbed supposed to be connected to the Internet without any restriction.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Narseo Vallina-Rodriguez</style></author><author><style face="normal" font="default" size="100%">A. Aucinas</style></author><author><style face="normal" font="default" size="100%">M. Almeida</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">Konstantina Papagiannaki</style></author><author><style face="normal" font="default" size="100%">Jon Crowcroft</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">RILAnalyzer: a Comprehensive 3G Monitor on Your Phone</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference (IMC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Daniele Apiletti</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Tania Cerquitelli</style></author><author><style face="normal" font="default" size="100%">Silvia Chiusano</style></author><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SEARUM: a cloud-based SErvice for Association RUle Mining</style></title><secondary-title><style face="normal" font="default" size="100%">The 11th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA-13)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">association rule mining</style></keyword><keyword><style  face="normal" font="default" size="100%">cloud-based service</style></keyword><keyword><style  face="normal" font="default" size="100%">distributed computing model</style></keyword><keyword><style  face="normal" font="default" size="100%">network data analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Large volumes of data are being produced by various modern applications at an ever increasing rate. These applications range from wireless sensors networks to social networks. The automatic analysis of such huge data volume is a challenging task since a large amount of interesting knowledge can be extracted. Association rule mining is an exploratory data analysis method able to discover interesting and hidden correlations among data. Since this data mining process is characterized by computationally intensive tasks, efficient distributed approaches are needed to increase its scalability. This paper proposes a novel cloud-based service, named SEARUM, to efficiently mine association rules on a distributed computing model. SEARUM consists of a series of distributed MapReduce jobs run in the cloud. Each job performs a different step in the association rule mining process. As a case study, the proposed approach has been applied to the network data scenario. The experimental validation, performed on two real network datasets, shows the effectiveness and the efficiency of&amp;nbsp;SEARUM in mining association rules on a distributed computing model.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitri Papadimitriou</style></author><author><style face="normal" font="default" size="100%">Dario Rossi</style></author><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Marco Milanesio</style></author><author><style face="normal" font="default" size="100%">Ernst Biersack</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Alessandro Capello</style></author><author><style face="normal" font="default" size="100%">Fabio Invernizzi</style></author><author><style face="normal" font="default" size="100%">Omar Jabr</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Benoit Donnet</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selection of Existing Probes and Datasets</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">active probes</style></keyword><keyword><style  face="normal" font="default" size="100%">existing probes</style></keyword><keyword><style  face="normal" font="default" size="100%">passive probes</style></keyword><keyword><style  face="normal" font="default" size="100%">probes</style></keyword><keyword><style  face="normal" font="default" size="100%">proxy probes</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D2.1</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The mPlane architecture has been designed to include the possibility to interface with existing systems and platforms. While most measurement platforms in existence target a very specific measurement use case (e.g., the discovery of the Internet's router-level topology, the continuous measurement of the RTT among host pairs, the exporting via SNMP of network state, etc.), there are platforms that have a large deployed base, with lot of data being at disposal, and/or continuously
collecting data. It would be a waste of resources to merely reproduce this effort within mPlane. Instead, mPlane aims at directly interfacing with existing systems and re-using their capabilities and data to feed measurement results to the mPlane intelligence. This document lists selected existing systems that are important for mPlane either for theoretical, conceptual or practical reasons, and that are part of the background of mPlane partners. A sub-set of these systems will be eventually incorporated into mPlane by developing the necessary interfaces. Others could be integrated by the means of proxy probes,
i.e., the conceptual component responsible for such interfacing. The main focus of this document is to elaborate the concept of proxy probes, enumerate the systems that will be possibly considered for interface (proxy probe) development, and to
give high level descriptions of the proxy probe design for these systems. The following list enumerates the systems that the consortium has chosen to include:
- QoF - a TCP-aware IPFIX flow meter  Cisco Ping and SLA Agents - commercial availability and basic network parameter agents  
- Tracebox - a tool for middlebox detection and identification
- Scamper - a sophisticated active probing tool
- MERLIN - a router-level topology discovery tool
- TopHat - a configurable measurement system on top of PlanetLab
- Tstat - a passive network monitoring tool
- BlockMon - a flexible network monitoring and analysis tool
- MisuraInternet - a QoS measurement system
- Firelog - a Firefox plugin to measure HTTP QoE
- Pytomo - an end-host-based video OoE measurement tool
- DATI - a high performance deep packet inspector
- MobiPerf - a tool for monitoring smartphone performance</style></abstract><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luigi Grimaudo</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Elena Baralis</style></author><author><style face="normal" font="default" size="100%">Ram Keralapura</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Self-Learning Classifier for Internet Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">The 5th IEEE International Traffic Monitoring and Analysis Workshop (TMA 2013)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Network visibility is a critical part of traffic engineering, network management, and security. Recently, unsupervised algorithms have been envisioned as a viable alternative&amp;nbsp;to automatically identify classes of traffic. However, the accuracy&amp;nbsp;achieved so far does not allow to use them for traffic classification&amp;nbsp;in practical scenario.&lt;br /&gt;In this paper, we propose SeLeCT, a Self-Learning Classifier&amp;nbsp;for Internet traffic. It uses unsupervised algorithms along with&amp;nbsp;an adaptive learning approach to automatically let classes of&amp;nbsp;traffic emerge, being identified and (easily) labeled. SeLeCT&amp;nbsp;automatically groups flows into pure (or homogeneous) clusters&amp;nbsp;using alternating simple clustering and filtering phases to remove&amp;nbsp;outliers. SeLeCT uses an adaptive learning approach to boost its&amp;nbsp;ability to spot new protocols and applications. Finally, SeLeCT&amp;nbsp;also simplifies label assignment (which is still based on some&amp;nbsp;manual intervention) so that proper class labels can be easily&amp;nbsp;discovered.&lt;br /&gt;We evaluate the performance of SeLeCT using traffic traces&amp;nbsp;collected in different years from various ISPs located in 3&amp;nbsp;different continents. Our experiments show that SeLeCT achieves&amp;nbsp;overall accuracy close to 98%. Unlike state-of-art classifiers, the&amp;nbsp;biggest advantage of SeLeCT is its ability to help discovering&amp;nbsp;new protocols and applications in an almost automated fashion.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gianni De Rosa</style></author><author><style face="normal" font="default" size="100%">Stefano Pentassuglia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Specification of mPlane Access Control and Data Protection Mechanisms</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">access control</style></keyword><keyword><style  face="normal" font="default" size="100%">anonymisation</style></keyword><keyword><style  face="normal" font="default" size="100%">authentication plane</style></keyword><keyword><style  face="normal" font="default" size="100%">privacy</style></keyword><keyword><style  face="normal" font="default" size="100%">security</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D1.2</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This document primarily defines security specifications for the mPlane architecture (in terms of authentication, access control and safe communications), on the basis of what specified in the D1.1. Also, it provides a description of the measures that can be adopted in order to guarantee the privacy of the data gathered through the probes. This aspect of the mPlane infrastructure must not be neglected, since from a legal point of view the users' right to privacy must be protected in any case. The techniques to be adopted are anonymization and aggregation, but utility of data decreases as the level of privacy increases, hence it is necessary to find a good trade-off. Two protocols are proposed for secure communications among components: TLS and SSH, which adopt respectively X.509 certificates and RSA keys for identity management. As the access control policy that will be adopted depends mostly on the mPlane administrators' choices, this document provides a survey of several approaches. The cross-domain and the mobile scenarios are also analyzed, providing solutions that can guarantee access control, security and privacy.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bagnulo  Marcelo</style></author><author><style face="normal" font="default" size="100%">Eardley Philip</style></author><author><style face="normal" font="default" size="100%">Burbridge Trevor</style></author><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Standardizing large-scale measurement platforms</style></title><secondary-title><style face="normal" font="default" size="100%">SIGCOMM Comput. Commun. Rev.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">design</style></keyword><keyword><style  face="normal" font="default" size="100%">ietf</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement platforms</style></keyword><keyword><style  face="normal" font="default" size="100%">standardization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2479957.2479967</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">58–63</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mirja Kuehlewind</style></author><author><style face="normal" font="default" size="100%">Sebastian Neuner</style></author><author><style face="normal" font="default" size="100%">Brian Trammell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On the state of ECN and TCP Options on the Internet</style></title><secondary-title><style face="normal" font="default" size="100%">Passive and Active Measurement Conference (PAM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2013</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Hong Kong</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span&gt;Explicit Congestion Notification (ECN) is a TCP/IP extension that can avoid packet loss and thus improve network performance. Though standardized in 2001, it is barely used in today’s Internet. This study, following on previous active measurement studies over the past decade, shows marked and continued increase in the deployment of ECN-capable servers, and usability of ECN on the majority of paths to such servers. We additionally present new measurements of ECN on IPv6, passive observation of actual ECN usage from flow data, and observations on other congestion-relevant TCP options (SACK, Timestamps and Window Scaling). We further present initial work on burst loss metrics for loss-based congestion control following from our findings.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Simoncelli, Davide</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Francesco Gringoli</style></author><author><style face="normal" font="default" size="100%">Saverio Niccolini</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Stream-monitoring with blockmon: convergence of network measurements and data analytics platforms</style></title><secondary-title><style face="normal" font="default" size="100%">SIGCOMM Comput. Commun. Rev.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">distributed computing</style></keyword><keyword><style  face="normal" font="default" size="100%">performance analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2479957.2479962</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">29–36</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Michele Garetto</style></author><author><style face="normal" font="default" size="100%">Paolo Giaccone</style></author><author><style face="normal" font="default" size="100%">Emilio Leonardi</style></author><author><style face="normal" font="default" size="100%">Saverio Niccolini</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Temporal locality in today's content caching: why it matters and how to model it</style></title><secondary-title><style face="normal" font="default" size="100%">ACM SIGCOMM Computer Communication Review</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The dimensioning of caching systems represents a difficult task in the design of infrastructures for content distribution in the current Internet. This paper addresses the problem of defining a realistic arrival process for the content requests generated by users, due its critical importance for both analytical and simulative evaluations of the performance of caching systems. First, with the aid of YouTube traces collected inside operational residential networks, we identify the characteristics of real traffic that need to be considered or can be safely neglected in order to accurately predict the performance of a cache. Second, we propose a new parsimonious traffic model, named the Shot Noise Model (SNM), that enables users to natively capture the dynamics of content popularity, whilst still being suf- ficiently simple to be employed effectively for both analytical and scalable simulative studies of caching systems. Finally, our results show that the SNM presents a much better solution to account for the temporal locality observed in real traffic compared to existing approaches.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><section><style face="normal" font="default" size="100%">5</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Finamore, Alessandro</style></author><author><style face="normal" font="default" size="100%">Mellia, Marco</style></author><author><style face="normal" font="default" size="100%">Gilani, Zafar</style></author><author><style face="normal" font="default" size="100%">Papagiannaki, Konstantina</style></author><author><style face="normal" font="default" size="100%">Erramilli, Vijay</style></author><author><style face="normal" font="default" size="100%">Grunenberger, Yan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Is There a Case for Mobile Phone Content Pre-staging?</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Ninth ACM Conference on Emerging Networking Experiments and Technologies (Best Short Paper Award)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">content pre-staging</style></keyword><keyword><style  face="normal" font="default" size="100%">mobile networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2535372.2535414</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY, USA</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4503-2101-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Content caching is a fundamental building block of the Internet. Caches are widely deployed at network edges to improve performance for end-users, and to reduce load on web servers and the backbone network. Considering mobile 3G/4G networks, however, the bottleneck is at the access link, where bandwidth is shared among all mobile terminals. As such, per-user capacity cannot grow to cope with the traffic demand. Unfortunately, caching policies would not reduce the load on the wireless link which would have to carry multiple copies of the same object that is being downloaded by multiple mobile terminals sharing the same access link.&lt;/p&gt;&lt;p&gt;In this paper we investigate if it is worth to push the caching paradigm even farther. We hypothesize a system in which mobile terminals implement a local cache, where popular content can be pushed/pre-staged. This exploits the peculiar broadcast capability of the wireless channels to replicate content &quot;for free&quot; on all terminals, saving the cost of transmitting multiple copies of those popular objects. Relying on a large data set collected from a European mobile carrier, we analyse the content popularity characteristics of mobile traffic, and quantify the benefit that the push-to-mobile system would produce. We found that content pre-staging, by proactively and periodically broadcasting &quot;bundles&quot; of popular objects to devices, allows to both greatly i) improve users' performance and ii) reduce up to 20% (40%) the downloaded volume (number of requests) in optimistic scenarios with a bundle of 100 MB. However, some technical constraints and content characteristics could question the actual gain such system would reach in practice.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">C. Chirichella</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">To the Moon and back: are Internet bufferbloat delays really that large</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE INFOCOM Workshop on Traffic Monitoring and Analysis  (TMA'13)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/~drossi/paper/rossi13tma-a.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Stephan Neuhaus</style></author><author><style face="normal" font="default" size="100%">Francesco Matera</style></author><author><style face="normal" font="default" size="100%">Ernst Biersack</style></author><author><style face="normal" font="default" size="100%">Antonio Barbuzzi</style></author><author><style face="normal" font="default" size="100%">Saverio Niccolini</style></author><author><style face="normal" font="default" size="100%">Mohamed Ahmed</style></author><author><style face="normal" font="default" size="100%">Maurizio Dusi</style></author><author><style face="normal" font="default" size="100%">Tivadar Szemethy</style></author><author><style face="normal" font="default" size="100%">Balazs Szabo</style></author><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">A Bär</style></author><author><style face="normal" font="default" size="100%">Konstantina Papagiannaki</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">Ilias Leontiadis</style></author><author><style face="normal" font="default" size="100%">Rolf Winter</style></author><author><style face="normal" font="default" size="100%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Giovanna Carofiglio</style></author><author><style face="normal" font="default" size="100%">Samir Ghamri-Doudane</style></author><author><style face="normal" font="default" size="100%">Diego Perino</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use Case Elaboration and Requirements Specification</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">architecture</style></keyword><keyword><style  face="normal" font="default" size="100%">measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">platform</style></keyword><keyword><style  face="normal" font="default" size="100%">scenario</style></keyword><keyword><style  face="normal" font="default" size="100%">use case</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2013</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">D1.1</style></number><publisher><style face="normal" font="default" size="100%">mPlane Consortium</style></publisher><pub-location><style face="normal" font="default" size="100%">Torino</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span&gt;The document defines the requirements for the mPlane architecture on the background of a set of scenarios explored by the consortium, a survey of existing comparable measurement systems and platforms and applicable standards therefore, and a set of architectural first principles drawn from the description of work and the consortium's experience.&amp;nbsp;As mPlane is intended to be a fully flexible measurement platform, freely integrating existing probes and repositories with ones to be developed in the project, this document is primarily concerned with the definition of interfaces among mPlane components. While it does enumerate capabilities to be provided by these components, these are primarily intended to ensure the platform has the flexibility required to meet all the scenarios envisioned; the enumerations of measurements, metrics, data types, and other component capabilities are therefore not to be construed to limit the scope of work on components within the project to just those scenarios treated in this document; nor do the scenarios enumerated here define the capabilities to be demonstrated in the project's integrated trial.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Public Deliverable</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">M. Seufert</style></author><author><style face="normal" font="default" size="100%">R. Schatz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks</style></title><secondary-title><style face="normal" font="default" size="100%">31st IFIP Performance</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">3G Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">MOS</style></keyword><keyword><style  face="normal" font="default" size="100%">QoE Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Stallings</style></keyword><keyword><style  face="normal" font="default" size="100%">YouTube</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;YouTube is changing the way operators manage network performance monitoring. In this paper we introduce YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G customers watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Narseo Vallina-Rodriguez</style></author><author><style face="normal" font="default" size="100%">Jay Shah</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Yan Grunenberger</style></author><author><style face="normal" font="default" size="100%">Konstantina Papagiannaki</style></author><author><style face="normal" font="default" size="100%">Hamed Haddadi</style></author><author><style face="normal" font="default" size="100%">Jon Crowcroft</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Breaking for commercials: characterizing mobile advertising</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2012 ACM conference on Internet measurement conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">advertisement</style></keyword><keyword><style  face="normal" font="default" size="100%">caching</style></keyword><keyword><style  face="normal" font="default" size="100%">cellular</style></keyword><keyword><style  face="normal" font="default" size="100%">energy</style></keyword><keyword><style  face="normal" font="default" size="100%">smartphones</style></keyword><keyword><style  face="normal" font="default" size="100%">traffic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2398776.2398812</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston, MA</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4503-1705-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 1&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;Mobile phones and tablets can be considered as the first incarnation of the post-PC era. Their explosive adoption rate has been driven by a number of factors, with the most signifcant influence being applications (apps) and app markets. Individuals and organizations are able to develop and publish apps, and the most popular form of monetization is mobile advertising. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;The mobile advertisement (ad) ecosystem has been the target of prior research, but these works typically focused on a small set of apps or are from a user privacy perspective. In this work we make use of a unique, anonymized data set corresponding to one day of traffic for a major European mobile carrier with more than 3 million subscribers. We further take a principled approach to characterize mobile ad traffic along a number of dimensions, such as overall traffic, frequency, as well as possible implications in terms of en- ergy on a mobile device. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;Our analysis demonstrates a number of inefficiencies in today’s ad delivery. We discuss the benefits of well-known techniques, such as pre-fetching and caching, to limit the energy and network signalling overhead caused by current systems. A prototype im- plementation on Android devices demonstrates an improvement of 50% in terms of energy consumption for offline ad-sponsored apps while limiting the amount of ad related traffic.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Nicolas Bermudez</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio M Munafo'</style></author><author><style face="normal" font="default" size="100%">Ram Keralapura</style></author><author><style face="normal" font="default" size="100%">Antonio Nucci</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DNS to the rescue: Discerning Content and Services in a Tangled Web</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference 2012</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNS</style></keyword><keyword><style  face="normal" font="default" size="100%">mPlane</style></keyword><keyword><style  face="normal" font="default" size="100%">passive measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">WP2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dl.acm.org/citation.cfm?id=2398776.2398819&amp;coll=DL&amp;dl=GUIDE&amp;CFID=225051145&amp;CFTOKEN=42401286</style></url></web-urls></urls><edition><style face="normal" font="default" size="100%">ACM</style></edition><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston, MA</style></pub-location><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">413-426</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4503-1705-4</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 1&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;A careful perusal of the Internet evolution reveals two major trends - explosion of cloud-based services and video stream- ing applications. In both of the above cases, the owner (e.g., CNN, YouTube, or Zynga) of the content and the organiza- tion serving it (e.g., Akamai, Limelight, or Amazon EC2) are decoupled, thus making it harder to understand the associ- ation between the content, owner, and the host where the content resides. This has created a tangled world wide web that is very hard to unwind, impairing ISPs’ and network administrators’ capabilities to control the traffic flowing in their networks. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;In this paper, we present DN-Hunter, a system that lever- ages the information provided by DNS traffic to discern the tangle. Parsing through DNS queries, DN-Hunter tags traf- fic flows with the associated domain name. This association has several applications and reveals a large amount of use- ful information: (&lt;/span&gt;&lt;span&gt;i&lt;/span&gt;&lt;span&gt;) Provides a fine-grained traffic visibility even when the traffic is encrypted (i.e., TLS/SSL flows), thus enabling more effective policy controls, (&lt;/span&gt;&lt;span&gt;ii&lt;/span&gt;&lt;span&gt;) Identifies flows even before the flows begin, thus providing superior net- work management capabilities to administrators, (&lt;/span&gt;&lt;span&gt;iii&lt;/span&gt;&lt;span&gt;) Un- derstand and track (over time) different CDNs and cloud providers that host content for a particular resource, (&lt;/span&gt;&lt;span&gt;iv&lt;/span&gt;&lt;span&gt;) Discern all the services/content hosted by a given CDN or cloud provider in a particular geography and time interval, and (&lt;/span&gt;&lt;span&gt;v&lt;/span&gt;&lt;span&gt;) Provides insights into all applications/services run- ning on any given layer-4 port number. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;We conduct extensive experimental analysis and show re- sults from real traffic traces (including FTTH and 4G ISPs) that support our hypothesis. Simply put, the information provided by DNS traffic is one of the key components re- quired for understanding the tangled web, and bringing the ability to effectively manage network traffic back to the op- erators.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract><num-vols><style face="normal" font="default" size="100%">1</style></num-vols></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brian Trammell</style></author><author><style face="normal" font="default" size="100%">Dominik Schatzmann</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">On Flow Concurrency in the Internet and its Implications for Capacity Sharing</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Second ACM CoNext Capacity Sharing Workshop (CSWS)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2012</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Nice, France</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio M Munafo'</style></author><author><style face="normal" font="default" size="100%">Anna Sperotto</style></author><author><style face="normal" font="default" size="100%">Ramin Sadre</style></author><author><style face="normal" font="default" size="100%">Aiko Pras</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Inside Dropbox: Understanding Personal Cloud Storage Services</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference - IMC</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Dropbox</style></keyword><keyword><style  face="normal" font="default" size="100%">passive measurement</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dl.acm.org/citation.cfm?id=2398776.2398827&amp;coll=DL&amp;dl=GUIDE&amp;CFID=225051145&amp;CFTOKEN=42401286</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston, MA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 1&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;Personal cloud storage services are gaining popularity. With a rush of providers to enter the market and an increasing of- fer of cheap storage space, it is to be expected that cloud storage will soon generate a high amount of Internet traffic. Very little is known about the architecture and the perfor- mance of such systems, and the workload they have to face. This understanding is essential for designing efficient cloud storage systems and predicting their impact on the network. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;This paper presents a characterization of Dropbox, the leading solution in personal cloud storage in our datasets. By means of passive measurements, we analyze data from four vantage points in Europe, collected during 42 consecu- tive days. Our contributions are threefold: Firstly, we are the first to study Dropbox, which we show to be the most widely-used cloud storage system, already accounting for a volume equivalent to around one third of the YouTube traffic at campus networks on some days. Secondly, we character- ize the workload users in different environments generate to the system, highlighting how this reflects on network traf- fic. Lastly, our results show possible performance bottle- necks caused by both the current system architecture and the storage protocol. This is exacerbated for users connected far from storage data-centers. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;All measurements used in our analyses are publicly avail- able in anonymized form at the SimpleWeb trace repository: &lt;/span&gt;&lt;span&gt;&lt;a href=&quot;http://traces.simpleweb.org/dropbox/&quot; title=&quot;Linkification: http://traces.simpleweb.org/dropbox/&quot; class=&quot;linkification-ext&quot; style=&quot;color: #006620;&quot;&gt;http://traces.simpleweb.org/dropbox/&lt;/a&gt;&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">YiXi Gong</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">C. Testa</style></author><author><style face="normal" font="default" size="100%">S. Valenti</style></author><author><style face="normal" font="default" size="100%">D. Taht</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interaction or Interference: can AQM and Low Priority Congestion Control Successfully Collaborate</style></title><secondary-title><style face="normal" font="default" size="100%">ACM CoNEXT, Extended Abstract</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.enst.fr/drossi/paper/rossi12conext.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Heterogeneity in the Internet ecosystem sometimes turns interaction into interference. Over the years, active queue management (AQM) and end-to-end low-priority congestion control (LPCC) have been proposed as alternative solutions to counter the persistently full buffer problem -- that recently became popular under the ``bufferbloat'' term. In this work, we point out the existence of a negative interplay among AQM and LPCC techniques. Intuitively, as AQM is designed to penalize the most aggressive flows it mainly hit best effort TCP: it follows that LPCC is not able to maintain its low priority, thus becoming as aggressive as TCP. By an extended set of simulation on various AQM policies and LPCC protocols, including the very recent CoDel AQM and LEDBAT LPCC proposals, we point out that this interference is quite universal and deserves further attention.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alessandro Finamore</style></author><author><style face="normal" font="default" size="100%">Vinicius Gehlen</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio M Munafo'</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The need for an intelligent measurement plane: The example of time-variant CDN policies</style></title><secondary-title><style face="normal" font="default" size="100%">Telecommunications Network Strategy and Planning Symposium (NETWORKS), 2012 XVth International </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Facebook</style></keyword><keyword><style  face="normal" font="default" size="100%">Google</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Organizations</style></keyword><keyword><style  face="normal" font="default" size="100%">Servers</style></keyword><keyword><style  face="normal" font="default" size="100%">Streaming media</style></keyword><keyword><style  face="normal" font="default" size="100%">Throughput</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2012</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">1 - 6 </style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we characterize how web-based services are delivered by large organizations in today's Internet. Taking advantage oftwo week-long data sets separated in time by 10 months and reporting the web activity of more than 10,000 ADSL residential customers, we identify the services offered by large organizations like Google, Akamai and Amazon. We then compare theevolution of both policies used to serve requests, and the infrastructure they use to match the users' demand. Results depict anovercrowded scenario in constant evolution. Big-players are more and more responsible for the majority of the volume and a plethora of other organizations offering similar or more specific services through different CDNs and traffic policies. Unfortunately, no standard tools and methodologies are available to capture and expose the hidden properties of this in constant evolution picture. A deeper understanding of such dynamics is however fundamental to improve the performance of current and future Internet. To this extend, we claim the need for a Internet-wide, standard, flexible and intelligent measurement plane to be added tothe current Internet infrastructure.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pedro Maria Santiago del Rio</style></author><author><style face="normal" font="default" size="100%">D Rossi</style></author><author><style face="normal" font="default" size="100%">Francesco Gringoli</style></author><author><style face="normal" font="default" size="100%">Lorenzo Nava</style></author><author><style face="normal" font="default" size="100%">Luca Salgarelli</style></author><author><style face="normal" font="default" size="100%">Javier Aracil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wire-speed statistical classification of network traffic on commodity hardware</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Internet Measurement Conference (IMC)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2012</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper we present a software-based traffic classification engine running on commodity multi-core hardware, able to process in real-time aggregates of up to 14.2Mpps over a single 10Gbps interface -- i.e., the maximum possible packet rate over a 10Gbps Ethernet links given the minimum frame size of 64Bytes. This significant advance with respect to the current state of the art in terms of achieved classification rates are made possible by: (i) the use of an improved network driver, PacketShader, to efficiently move batches of packets from the NIC to the main CPU; (ii) the use of lightweight statistical classification techniques exploiting the size of the first few packets of every observed flow; (iii) a careful tuning of critical parameters of the hardware environment and the software application itself.&lt;/p&gt;</style></abstract></record></records></xml>