@inproceedings {Van2016, title = {A Brief History of MPLS Usage in IPv6}, booktitle = {Passive and Active Measurement Conference (PAM)}, year = {2016}, month = {03/2016}, abstract = {

Recent researches have stated the fast deployment of IPv6. It\ has been demonstrated that IPv6 grows much faster, being so more and more\ adopted by both Internet service providers but also by servers and end-hosts.\ In parallel, researches have been conducted to discover and assess the usage of\ MPLS tunnels. Indeed, recent developments in the ICMP protocol make certain
categories of MPLS tunnels transparent to traceroute probing. However, these\ studies focus only on IPv4, where MPLS is strongly deployed.

In this paper, we provide a first look at how MPLS is used under IPv6\ networks using traceroute data collected by CAIDA.\ We have observed, at the first glance, that the MPLS deployment and usage seem to greatly differ between IPv4 and IPv6,\ in particular in the way MPLS label stacks are used. While label stacks are not that frequent\ in IPv4 (and mostly correspond to a VPN usage), they are prevalent in IPv6. \ 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. \ 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).

}, keywords = {6PE tunnels, IPv6, LSE Stack, MPLS}, author = {Yves Vanaubel and Pascal M{\'e}rindol and Jean-Jacques Pansiot and Benoit Donnet} } @article {Teg2016, title = {Experimental investigation on TCP throughput behavior in Optical Fiber Access Networks}, journal = {Fiber and Integrated Optics}, year = {2016}, type = {Journal article.}, author = {Edion Tego and Francesco Matera and Donato Del Buono} } @inproceedings {Pap2016a, title = {Mixed-Integer Optimization for the Combined capacitated Facility Location-Routing Problem}, booktitle = {International Conference on the Design of Reliable Communication Networks (DRCN) 2016}, year = {2016}, publisher = {IEEE XPlore}, organization = {IEEE XPlore}, address = {Paris, France}, author = {Dimitri Papadimitriou and Didier Colle and Piet Demeester} } @article {Cas2016, title = {Unveiling Network and Service Performance Degradation in the Wild with mPlane}, journal = {IEEE Communications Magazine - Network Testing Series}, year = {2016}, abstract = {

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.

}, author = {Pedro Casas and Pierdomenico Fiadino and Sarah Wassermann and Stefano Traverso and Alessandro D{\textquoteright}Alconzo and Edion Tego and Francesco Matera and Marco Mellia} } @inproceedings {Fia2015b, title = {Challenging Entropy-based Anomaly Detection and Diagnosis in Cellular Networks}, booktitle = {ACM SIGCOMM}, year = {2015}, author = {Pierdomenico Fiadino and Alessandro D{\textquoteright}Alconzo and Mirko Schiavone and Pedro Casas} } @article {D61, title = {Demonstration Plan}, number = {D6.1}, year = {2015}, month = {01/2015}, type = {Public Deliverable}, issn = {D6.1}, author = {Pedro Casas and Edion Tego and Francesco Matera and Maurizio Dusi and A. Bakay and Balazs Szabo and G. Rozsa and Stefano Traverso and Ilias Leontiadis and L. Baltrunas and Yan Grunenberger and Andrea Fregosi and A. Kahveci and Eike Kowallik and G. Mattellini and C. Meregalli and Stefano Raffaglio and M. Russo and Andrea Sannino and M. Scarpino} } @article {2016, title = {HFSP: Bringing size-based scheduling to Hadoop}, journal = {IEEE Transaction on Cloud Computing}, year = {2015}, author = {Mario Pastorelli and Damiano Carra and Matteo Dell{\textquoteright}Amico and Pietro Michiardi} } @inproceedings {Dim2015, title = {Identifying the Root Cause of Video Streaming Issues on Mobile Devices}, booktitle = {CoNext}, year = {2015}, author = {G. Dimopoulos and I. Leontiadis and P. Barlet-Ros and K. Papagiannaki and P. Steenkiste} } @inproceedings {DR:TRAC-15, title = {Impact of Carrier-Grade NAT on Web Browsing}, booktitle = { 6th International Workshop on TRaffic Analysis and Characterization (TRAC) - The paper won the BEST PAPER award}, year = {2015}, month = {08/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Dobrovnik, Croatia}, abstract = {

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{\textquoteright} 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{\textquoteright} web browsing experience. Our results testify that CGN is a mature and stable technology as, if properly deployed, it does not harm users{\textquoteright} 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{\textquoteright} browsing are otherwise unperturbed. Interestingly, we also observe that CGN protects customers from unsolicited, often malicious, traffic.

}, url = {http://www.enst.fr/~drossi/paper/rossi15trac.pdf}, author = {Bocchi, Enrico and Safari, Ali and Traverso, Stefano and Finamore, Alessandro and Di Gennaro, Valeria and Mellia, Marco and Munafo, Maurizio and Rossi, Dario} } @inproceedings {Yon2015, title = {A Lightweight Network Proximity Service Based On Neighborhood Models}, booktitle = {22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT)}, year = {2015}, month = {11/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Luxembourg}, abstract = {

This paper proposes a network proximity service\ based on the neighborhood models used in recommender systems.\ Unlike previous approaches, our service infers network proximity\ without trying to recover the latency between network nodes. By\ asking each node to probe a number of landmark nodes which\ can be servers at Google, Yahoo and Facebook, etc., a simple\ proximity measure is computed and allows the direct ranking\ and rating of network nodes by their proximity to a target node.\ The service is thus lightweight and can be easily deployed in\ e.g. P2P and CDN applications. Simulations on existing datasets\ and experiments with a deployment over PlanetLab showed\ that our service achieves an accurate proximity inference that\ is comparable to state-of-the-art latency prediction approaches,\ while being much simpler.

}, author = {Liao, Yongjun and Du, Wei and Leduc, Guy} } @inproceedings {Van2015, title = {MPLS Under the Microscope: Revealing Actual Transit Path Diversity}, booktitle = {Internet Measurement Conference (IMC)}, year = {2015}, month = {10/2015}, abstract = {

Traffic Engineering (TE) is one of the keys for improving packet forwarding in\ the Internet. It allows IP network operators to finely tune their forwarding\ paths according to various customer needs. One of the most popular tool\ available today for optimizing the use of networking resources is MPLS. On the\ one hand, operators may use MPLS and label distribution mechanisms such as RSVP-TE\ in conjunction with BGP to define multiple transit paths (for a given edge pair)
verifying different constraints on their network. On the other hand, when\ operators simply enable LDP for distributing MPLS labels in order to improve the\ scalability of their network, another kind of path diversity may appear thanks\ to the ECMP feature of IGP routing.

In this paper, using an MPLS labels analysis, we demonstrate that it is possible\ to better understand the transit path diversity deployed within a given ISP.\ More specifically, we introduce the Label Pattern Recognition (LPR) algorithm, a\ method for analyzing traceroute data including MPLS information. LPR reveals\ the actual usage of MPLS according to the inferred label distribution protocol and\ is able to make the distinction between ECMP and TE multi-path forwarding.\ Based on an extensive and longitudinal traceroute dataset obtained from CAIDA,
we apply LPR and find that each ISP behavior is really specific in regard to its\ MPLS usage. In particular, we are able to observe independently for each ISP\ the MPLS path diversity and usage, and its evolution over time.\ Globally speaking, the main outcomes of our study are that (i) the usage of\ MPLS has been increasing over the the last five years with basic encapsulation\ being predominant, (ii) path diversity is mainly provided thanks to ECMP and\ LDP, and, (iii), TE using MPLS is as common as MPLS without path diversity.

}, keywords = {ECMP, LDP, MPLS, multipath, network discovery, RSVP-TE, traceroute, traffic engineering}, author = {Yves Vanaubel and Pascal M{\'e}rindol and Jean-Jacques Pansiot and Benoit Donnet} } @inproceedings {7145326, title = {Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks}, booktitle = {IFIP Networking Conference (IFIP Networking), 2015}, year = {2015}, month = {May}, keywords = {Cellular Networks, Content Delivery Networks, Europe, Facebook, Internet, IP networks, Network Measurements, Online Social Networks, Organizations, Servers, WhatsApp}, doi = {10.1109/IFIPNetworking.2015.7145326}, author = {Fiadino, Pierdomenico and Casas, Pedro and Schiavone, Mirko and D{\textquoteright}Alconzo, Alessandro} } @article {7096995, title = {Personal Cloud Storage Benchmarks and Comparison}, journal = {Cloud Computing, IEEE Transactions on}, volume = {PP}, year = {2015}, pages = {1-1}, abstract = {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.}, keywords = {Benchmark testing, Cloud computing, Cloud storage, Computers, Google, Measurements, Performance, Servers, Synchronization}, issn = {2168-7161}, doi = {10.1109/TCC.2015.2427191}, author = {Enrico Bocchi and Idilio Drago and Marco Mellia} } @inproceedings {Boc2015, title = {Personal Cloud Storage: Usage, Performance and Impact of Terminals }, booktitle = {4th IEEE International Conference on Cloud Networking (IEEE CloudNet 2015)}, year = {2015}, month = {10/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Niagara Falls, Canada}, abstract = {

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.

}, keywords = {Cloud storage, Monitoring}, url = {http://www.ieee-cloudnet.org/program.html}, author = {Enrico Bocchi and Idilio Drago and Marco Mellia} } @article {Wei2014, title = {Rating Network Paths for Locality-Aware Overlay Construction and Routing}, journal = {IEEE/ACM Transactions on Networking}, volume = {23}, year = {2015}, month = {10/2015}, chapter = {1661}, abstract = {

This paper investigates the rating of network paths,\ i.e. acquiring quantized measures of path properties such as\ round-trip time and available bandwidth. Comparing to finegrained\ measurements, coarse-grained ratings are appealing in\ that they are not only informative but also cheap to obtain.

Motivated by this insight, we firstly address the scalable\ acquisition of path ratings by statistical inference. By observing\ similarities to recommender systems, we examine the applicability\ of solutions to recommender system and show that our\ inference problem can be solved by a class of matrix factorization\ techniques. A technical contribution is an active and progressive\ inference framework that not only improves the accuracy by\ selectively measuring more informative paths but also speeds\ up the convergence for available bandwidth by incorporating its\ measurement methodology.

Then, we investigate the usability of rating-based network\ measurement and inference in applications. A case study is\ performed on whether locality awareness can be achieved for\ overlay networks of Pastry and BitTorrent using inferred ratings.

We show that such coarse-grained knowledge can improve the\ performance of peer selection and that finer granularities do not\ always lead to larger improvements.

}, keywords = {matrix factorization, network inference, rating-based network measurement, recommender system}, author = {Du, Wei and Liao, Yongjun and Tao, Narisu and Geurts, Pierre and Fu, Xiaoming and Leduc, Guy} } @inproceedings {Fia2015a, title = {RCATool - A Framework for Detecting and Diagnosing Anomalies in Cellular Networks}, booktitle = {27th International Teletraffic Congress (ITC)}, year = {2015}, author = {Pierdomenico Fiadino and Alessandro D{\textquoteright}Alconzo and Mirko Schiavone and Pedro Casas} } @inproceedings {Ede2015a, title = {Towards a Middlebox Policy Taxonomy: Path Impairments}, booktitle = {International Workshop on Network Science for Communication Networks (NetSciCom)}, year = {2015}, month = {04/2015}, abstract = {

Recent years have seen the rise of middleboxes, such as firewalls, NATs, proxies,\ or Deep Packet Inspectors. Those middleboxes play an important role in today{\textquoteright}s\ Internet, including enterprise networks and cellular networks. However, despite\ their huge success in modern network architecture, they have a negative impact\ on the Internet evolution as they can slow down the TCP protocol evolution and its\ extensions. Making available a summary of the potential middlebox network\ interferences is of the highest importance as it could allow researchers to\ confront their new transport protocol to potential issues caused by middleboxes.\ And, consequently, allowing again innovation in the Internet.

This is exactly what we tackle in this paper. We propose a path impairment\ oriented middlebox taxonomy that aims at categorizing the initial purpose of a\ middlebox policy as well as its potential unexpected complications. Based on a\ measurement campaign on IPv4 and IPv6 networks, we confront our taxonomy to the\ real world. Our dataset is freely available.

}, keywords = {classification, IPv6, middleboxes, path impairment, tracebox}, author = {Korian Edeline and Benoit Donnet} } @inproceedings {Fia2015, title = {Towards Automatic Detection and Diagnosis of Internet Service Anomalies via DNS Traffic Analysis}, booktitle = {6th International Workshop on Traffic Analysis and Characterization (TRAC)}, year = {2015}, author = {Pierdomenico Fiadino and Alessandro D{\textquoteright}Alconzo and Mirko Schiavone and Pedro Casas} } @inproceedings {Was2015, title = {Towards DisNETPerf: a Distributed Internet Paths Performance Analyzer}, booktitle = {The 11th International Conference on emerging Networking EXperiments and Technologies - CoNEXT 2015}, year = {2015}, month = {11/2015}, abstract = {

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 \ 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.

}, author = {Sarah Wassermann and Pedro Casas and Benoit Donnet} } @inproceedings {Thi2015a, title = {Tracking Middleboxes in the Mobile World with TraceboxAndroid}, booktitle = {7th International Workshop on Traffic Monitoring and Analysis (TMA)}, year = {2015}, month = {04/2015}, abstract = {

Middleboxes are largely deployed over cellular networks. It is known that they\ might disrupt network performance, expose users to security issues, and harm\ protocols deployability. Further, hardly any network measurements tools for\ smartphones are able to infer middlebox behaviors, specially if one cannot\ control both ends of a path. In this paper, we present TraceboxAndroid a
proof-of-concept measurement application for Android mobile devices\ implementing the tracebox algorithm. It aims at diagnosing middlebox-impaired\ paths by detecting and locating rewriting middleboxes. We analyze a dataset\ sample to highlight the range of opportunities offered by TraceboxAndroid. We\ show that TraceboxAndroid can be useful for mobile users as well as for the
research community.

}, keywords = {Android, tracebox}, author = {Valentin Thirion and Korian Edeline and Benoit Donnet} } @article {Dus2014a, title = {Algorithm and Scheduler Design and Implementation}, year = {2014}, month = {09/2014}, keywords = {algorithm design, job scheduler, mPlane software, repository tools}, isbn = {D3.3}, issn = {D3.3}, author = {Maurizio Dusi and Saverio Niccolini and Sofia Nikitaki and Daniele Apiletti and Elena Baralis and Alessandro Finamore and Luigi Grimaudo and Stefano Traverso and Francesco Matera and Edion Tego and V, Guchev and Zied Ben Houidi and Pietro Michiardi and Marco Milanesio and YiXi Gong and Dario Rossi and Ilias Leontiadis and G, Dimopoulos and Tivadar Szemethy and A, Bakay and Arian B{\"a}r and Pedro Casas and Alessandro D{\textquoteright}Alconzo and Pierdomenico Fiadino} } @inproceedings {Cas2014d, title = {On the Analysis of QoE-based Performance Degradation in YouTube Traffic}, booktitle = {10th International Conference on Network and Service Management, CNSM 2014}, year = {2014}, month = {11/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Rio de Janeiro, Brazil}, abstract = {

YouTube is the most popular service in today{\textquoteright}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{\textquoteright} 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{\textquoteright}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{\textquoteright}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.

}, keywords = {clustering, Content Delivery Networks, Empirical Entropy, Performance Degradation, Quality of Experience, YouTube}, author = {Pedro Casas and Alessandro D{\textquoteright}Alconzo and Pierdomenico Fiadino and Arian B{\"a}r and Alessandro Finamore} } @inproceedings {Fia, title = {Characterizing Web Services Provisioning via CDNs: The Case of Facebook}, booktitle = {5th International Workshop on TRaffic Analysis and Characterization}, year = {2014}, month = {08/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Nicosia, Cyprus}, abstract = {

Today{\textquoteright}s Internet consists of massive scale web\ services and Content Delivery Networks (CDNs). This paper sheds\ light on the way major Internet-scale web services content is\ hosted and delivered. By analyzing a full month of HTTP traffic\ traces collected at the mobile network of a major European ISP,\ we characterize the paradigmatic case of Facebook, considering\ not only the traffic flows but also the main organizations and\ CDNs providing them. Our study serves the main purpose of\ better understanding how major web services are provisioned\ in today{\textquoteright}s Internet, paying special attention to the temporal\ dynamics of the service delivery and the interplays between the\ involved hosting organizations. To the best of our knowledge, this\ is the first paper providing such an analysis in mobile networks.

}, keywords = {Akamai, Content Delivery Networks, Facebook, HTTP Traffic, mobile networks}, author = {Pierdomenico Fiadino and Alessandro D{\textquoteright}Alconzo and Pedro Casas} } @article {D43, title = { Cross-check of Analysis Modules and Reasoner Interactions}, number = {D4.3}, year = {2014}, month = {10/2014}, type = {Deliverable}, keywords = {reasoner, WP4}, author = {Umberto Manferdini and Stefano Traverso and Marco Mellia and Edion Tego and Francesco Matera and Zied Ben Houidi and Marco Milanesio and Pietro Michiardi and Dario Rossi and D. Cicalese and D. Joumblatt and Jordan Aug{\'e} and Maurizio Dusi and Sofia Nikitaki and Mohamed Ahmed and Ilias Leontiadis and L. Baltrunas and M. Varvello and Pedro Casas and Alessandro D{\textquoteright}Alconzo and Benoit Donnet and W. Du and Guy Leduc and Y. Liao and Alessandro Capello and Fabrizio Invernizzi} } @article {D42, title = {Design of the Reasoner}, number = {D4.2}, year = {2014}, month = {06/2014}, type = {report}, keywords = {design, private deliverable, reasoner, WP4}, issn = {D4.2}, author = {Pedro Casas and Alessandro D{\textquoteright}Alconzo and Maurizio Dusi and Sofia Nikitaki and Mohamed Ahmed and Stefano Traverso and Marco Mellia and Daniele Apiletti and Luigi Grimaudo and Elena Baralis and Dario Rossi and D. Joumblatt and Alessandro Capello and M. D{\textquoteright}Ambrosio and Fabrizio Invernizzi and M. Ullio and Andrea Fregosi and Eike Kowallik and Stefano Raffaglio and Andrea Sannino and Marco Milanesio and Edion Tego and Francesco Matera and Tivadar Szemethy and Balazs Szabo and L. N{\'e}meth and Zied Ben Houidi and G. Dimopoulos and Ilias Leontiadis and Yan Grunenberger and L. Baltrunas and Michael Faath and Rolf Winter and Dimitri Papadimitriou} } @inproceedings {Fia2014, title = {On the Detection of Network Traffic Anomalies in Content Delivery Network Services}, booktitle = {ITC26}, year = {2014}, month = {09/2014}, address = {Karlskrona, Sweden}, author = {Pierdomenico Fiadino and Alessandro D{\textquoteright}Alconzo and Arian B{\"a}r and Alessandro Finamore and Pedro Casas} } @inbook {Geo2014, title = {Flow Management at Multi-Gbps: Tradeoffs and Lessons Learned}, booktitle = {Traffic Monitoring and Analysis}, series = {Lecture Notes in Computer Science}, volume = {8406}, year = {2014}, pages = {1-14}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, isbn = {978-3-642-54998-4}, doi = {10.1007/978-3-642-54999-1_1}, url = {http://dx.doi.org/10.1007/978-3-642-54999-1_1}, author = {Nassopulos, Georges and Rossi, Dario and Gringoli, Francesco and Nava, Lorenzo and Dusi, Maurizio and Santiago del Rio, PedroMaria} } @inproceedings {Cit2014, title = {On the Quality of BGP Route Collectors for iBGP Policy Inference}, booktitle = {IFIP Networking}, year = {2014}, month = {June 2014}, abstract = {

A significant portion of what is known about Internet routing stems out from\ public BGP datasets. For this reason, numerous research efforts were devoted to\ (i) assessing the (in)completeness of the datasets, (ii) identifying biases\ in the dataset, and (iii) augmenting data quality by optimally placing new\ collectors. However, those studies focused on techniques to extract information\ about the AS-level Internet topology.

In this paper, we show that considering different metrics influences the\ conclusions about biases and collector placement. Namely, we compare AS-level\ topology discovery with \iac inference. We find that the same datasets exhibit\ significantly diverse biases for these two metrics. For example, the sensitivity\ to the number and position of collectors is noticeably different. Moreover, for\ both metrics, the marginal utility of adding a new collector is strongly\ localized with respect to the proximity of the collector. Our results suggest\ that the {\textquoteleft}{\textquoteleft}optimal{\textquoteright}{\textquoteright} position for new collectors can only be defined with\ respect to a specific metric, hence posing a fundamental trade-off for\ maximizing the utility of extensions to the BGP data collection infrastructure.

}, keywords = {bias, iBGP policies, measurement, network topology}, author = {Luca Cittadini and Stefano Vissichio and Benoit Donnet} } @inproceedings {Teg2014, title = {Quality of Service Management based on Software Defined Networking Approach in wide GbE Networks}, booktitle = {Euromed}, year = {2014}, month = {11/2014}, abstract = {

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.

}, keywords = {GbE, PON, QoS, SDN}, author = {Edion Tego and Francesco Matera and Vincenzo Attanasio and Donato Del Buono} } @inproceedings {Dus2014, title = {Reactive Logic in Software-Defined Networking: Measuring Flow-Table Requirements}, booktitle = {5th International Workshop on TRaffic Analysis and Characterization (TRAC)}, year = {2014}, month = {2014}, address = {Nicosia, Cyprus}, author = {Maurizio Dusi and Roberto Bifulco and Francesco Gringoli and Fabian Schneider} } @inproceedings {EURECOM+4268, title = {Revisiting size-based scheduling with estimated job sizes}, booktitle = {{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}, year = {2014}, month = {03}, address = {{P}aris, {FRANCE}}, url = {http://www.eurecom.fr/publication/4268}, author = {Dell{\textquoteright}Amico, Matteo and Carra, Damiano and Pastorelli, Mario and Michiardi, Pietro} } @article {6975242, title = {When YouTube Does not Work - Analysis of QoE-Relevant Degradation in Google CDN Traffic}, journal = {Network and Service Management, IEEE Transactions on}, volume = {11}, year = {2014}, month = {Dec}, pages = {441-457}, keywords = {CDN distributed services, CDN server selection strategies, client-server systems, content delivery network, Content Delivery Networks, Degradation, dynamic approach, dynamic server selection strategies, end-user QoE, end-user quality of experience, European ISP, Google, Google CDN traffic, Google server selection strategies, IP networks, iterative structured process, load reduction, QoE-relevant anomaly characterization, QoE-relevant anomaly detection, QoE-relevant anomaly diagnosis, QoE-relevant degradation, Quality of Experience, Servers, social networking (online), statistical analysis, statistical analysis methodologies, Statistical Data Analysis, telecommunication traffic, Traffic Monitoring, Videos, watching experience improvement, YouTube, YouTube flow trace collection, YouTube QoE-relevant degradation, YouTube videos}, issn = {1932-4537}, doi = {10.1109/TNSM.2014.2377691}, author = {Casas, Pedro and D{\textquoteright}Alconzo, Alessandro and Fiadino, Pierdomenico and B{\"a}r, Arian and Finamore, Alessandro and Zseby, Tanja} } @inproceedings {A2014, title = {Who to Blame when YouTube is not Working? Detecting Anomalies in CDN Provisioned Services}, booktitle = {TRAC}, year = {2014}, month = {08/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Nicosia, Cyprus}, author = {Alessandro D{\textquoteright}Alconzo and Pedro Casas and Pierdomenico Fiadino and Arian B{\"a}r and Alessandro Finamore} } @inproceedings {Cas2014b, title = {YouTube All Around: Characterizing YouTube from Mobile and Fixed-line Network Vantage Points}, booktitle = {EuCNC}, year = {2014}, month = {06/2014}, address = {Bologna, IT}, author = {Pedro Casas and Pierdomenico Fiadino and Arian B{\"a}r and Alessandro D{\textquoteright}Alconzo and Alessandro Finamore and Marco Mellia} } @inproceedings {Cas2014c, title = {YouTube in the Move: Understanding the Performance of YouTube in Cellular Networks (BEST PAPER AWARD RUNNER UP)}, booktitle = {Wireless Days 2014}, year = {2014}, month = {11/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Rio de Janeiro, Brazil}, abstract = {

YouTube is the most popular and volume-dominant service in today{\textquoteright}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).

}, keywords = {Cellular Networks, Content Delivery Networks, End-device Measurements, QoE, Traffic Measurements, YouTube}, author = {Pedro Casas and Pierdomenico Fiadino and Andreas Sackl and Alessandro D{\textquoteright}Alconzo} } @article {Mic2013, title = {Basic Network Data Analysis}, number = {D3.1}, year = {2013}, month = {05/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, abstract = {

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.
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.
For each algorithm and use case, the input data and the initial state, the computation to run and the output produced are described.

}, keywords = {algorithms, big data, storage}, issn = {D3.1}, author = {Pietro Michiardi and Antonio Barbuzzi and Alessandro Finamore and Stefano Traverso and Daniele Apiletti and Elena Baralis and Tania Cerquitelli and Silvia Chiusano and Luigi Grimaudo and A. Rufini and Francesco Matera and A. Valentii and Maurizio Dusi and Mohamed Ahmed and Tivadar Szemethy and L. N{\'e}meth and R. Szalay and Ilias Leontiadis and Yan Grunenberger and P. Casas and Alessandro D{\textquoteright}Alconzo and A B{\"a}r and D Rossi and YiXi Gong} } @inproceedings {Dra2013, title = {Benchmarking Personal Cloud Storage}, booktitle = {Internet Measurement Conference - IMC}, year = {2013}, month = {10/2013}, publisher = {ACM}, organization = {ACM}, address = {Barcelona (ES)}, abstract = {

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 {\textendash} most of all {\textendash} 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.

}, keywords = {Active Measurements, Personal Cloud Storage}, doi = {10.1145/2504730.2504762}, url = {http://www.simpleweb.org/wiki/Cloud_benchmarks}, author = {Idilio Drago and Enrico Bocchi and Marco Mellia and Herman Slatman and Aiko Pras} } @article {Bar2013a, title = {Database Layer Design}, number = {D3.2}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, keywords = {big data, databases, repositories, storage}, issn = {D3.2}, author = {A B{\"a}r and P. Casas and Alessandro D{\textquoteright}Alconzo and Alessandro Finamore and Antonio Barbuzzi and Maurizio Dusi and Gianni De Rosa and Tivadar Szemethy and Ilias Leontiadis and D Rossi and Jordan Aug{\'e} and Marc-Oliver Buob} } @article {Pap2013, title = {Design of Analysis Modules}, number = {D4.1}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, keywords = {algorithms, analysis}, isbn = {D4.1}, issn = {D4.1}, author = {Dimitri Papadimitriou and Zied Ben-Houidi and Samir Ghamri-Doudane and D Rossi and M. Milanesio and P. Casas and Alessandro D{\textquoteright}Alconzo and Edion Tego and Francesco Matera and Maurizio Dusi and Tivadar Szemethy and L. M{\'a}th{\'e} and Alessandro Finamore and Stefano Traverso and Ilias Leontiadis and Yan Grunenberger and L. Baltrunas and Benoit Donnet and Guy Leduc and Y. Liao} } @article {Lia2013, title = {DMFSGD: A decentralized matrix factorization algorithm for network distance prediction}, journal = {IEEE/ACM Transactions on Networking}, volume = {21}, year = {2013}, month = {10/2013}, chapter = {1511}, abstract = {

The knowledge of end-to-end network distances is\ essential to many Internet applications. As active probing of all\ pairwise distances is infeasible in large-scale networks, a natural\ idea is to measure a few pairs and to predict the other ones\ without actually measuring them. This paper formulates the\ prediction problem as matrix completion where the unknown\ entries in a pairwise distance matrix constructed from a network\ are to be predicted. By assuming that the distance matrix has\ a low-rank characteristics, the problem is solvable by lowrank\ approximation based on matrix factorization. The new\ formulation circumvents the well-known drawbacks of existing\ approaches based on Euclidean embedding.

A new algorithm, so-called Decentralized Matrix Factorization\ by Stochastic Gradient Descent (DMFSGD), is proposed. By\ letting network nodes exchange messages with each other, the\ algorithm is fully decentralized and only requires each node\ to collect and to process local measurements, with neither\ explicit matrix constructions nor special nodes such as landmarks\ and central servers. In addition, we compared comprehensively\ matrix factorization and Euclidean embedding to demonstrate\ the suitability of the former on network distance prediction. We\ further studied the incorporation of a robust loss function and\ of non-negativity constraints. Extensive experiments on various\ publicly-available datasets of network delays show not only the\ scalability and the accuracy of our approach, but also its usability\ in real Internet applications.

}, keywords = {matrix completion, matrix factorization, network distance prediction, stochastic gradient descent}, author = {Yongjun Liao and Wei Du and Pierre Geurts and Guy Leduc} } @article {Cap2013, title = {First Data Collection Track Record}, number = {D5.1}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Private Deliverable}, address = {Torino}, keywords = {data sets, integration, measurement systems, scenarios, use cases}, author = {Alessandro Capello and Fabrizio Invernizzi and Omar Jabr and Dimitri Papadimitriou and Dario Rossi and YiXi Gong and Brian Trammell and Marco Milanesio and Ernst Biersack and Rolf Winter and Francesco Matera and Arianna Rufini and Edion Tego and Maurizio Dusi and Balazs Szabo and Tivadar Szemethy and Alessandro Finamore and Marco Mellia and Ilias Leontiadis and Benoit Donnet} } @inproceedings {Mar2013, title = {HFSP: Size-based Scheduling for Hadoop}, booktitle = {BIGDATA 2013, IEEE International Conference on BigData, October 6-9, 2013, Santa-Clara, CA, USA}, year = {2013}, month = {10}, url = {http://www.eurecom.fr/publication/4106}, author = {Pastorelli Mario and Barbuzzi Antonio and Carra Damiano and Dell{\textquoteright}Amico Matteo and Michiardi Pietro} } @inbook {Pap2013b, title = {Measurement-based Experimental Research Methodology}, booktitle = {Measurement Methodology and Tools}, series = {Lecture Notes in Computer Science Series}, volume = {7586}, year = {2013}, pages = {pp 5-22}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, issn = {978-3-642-41295-0}, doi = {10.1007/978-3-642-41296-7_2}, author = {D. Papadimitriou and L. F{\`a}brega and P. Vil{\`a} and D. Careglio and P. Demeester} } @article {Tra2013d, title = {mPlane Architecture Specification}, number = {D1.3}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, keywords = {architecture, measurement, platform, scenario, use case}, author = {Brian Trammell and Marco Mellia and Alessandro Finamore and Stefano Traverso and Tivadar Szemethy and Balazs Szabo and D Rossi and Benoit Donnet and Fabrizio Invernizzi and Dimitri Papadimitriou} } @inproceedings {Van2013, title = {Network Fingerprinting: TTL-Based Router Signature}, booktitle = {ACM/USENIX Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, address = {Barcelona, Spain}, abstract = {

Fingerprinting networking equipment has many potential applications and benefits\ in network management and security. More generally, it is useful for the\ understanding of network structures and their behaviors. In this paper, we\ describe a simple fingerprinting mechanism based on the initial TTL values used\ by routers to reply to various probing messages. We show that main classes
obtained using this simple mechanism are meaningful to distinguish routers\ platforms. Besides, it comes at a very low additional cost compared to standard\ active topology discovery measurements. As a proof of concept, we apply our\ method to gain more insight on the behavior of MPLS routers and to, thus, more\ accurately quantify their visible/invisible deployment.

}, keywords = {fingerprinting, initial TTL, MPLS router signature, network discovery}, doi = {10.1145/2504730.2504761}, author = {Yves Vanaubel and Jean-Jacques Pansiot and Pascal M{\'e}rindol and Benoit Donnet} } @inproceedings {Van2013a, title = {Network Fingerprinting: TTL-Based Router Signatures}, booktitle = {ACM Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, address = {Barcelona, Spain}, abstract = {

Fingerprinting networking equipment has many potential applications and benefits\ in network management and security. More generally, it is useful for the\ understanding of network structures and their behaviors. In this paper, we\ describe a simple fingerprinting mechanism based on the initial TTL values used\ by routers to reply to various probing messages. We show that main classes\ obtained using this simple mechanism are meaningful to distinguish routers
platforms. Besides, it comes at a very low additional cost compared to standard\ active topology discovery measurements. As a proof of concept, we apply our\ method to gain more insight on the behavior of MPLS routers and to, thus, more\ accurately quantify their visible/invisible deployment.

}, keywords = {fingerprinting, initial TTL, MPLS, network discovery, router signatures}, author = {Yves Vanaubel and Jean-Jacques Pansiot and Pascal M{\'e}rindol and Benoit Donnet} } @article {Dus2013, title = {Plans for Using and Disseminating mPlane Knowledge}, number = {D7.2}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, keywords = {dissemination, exploitation, open-source software, publications, standardization}, issn = {D7.2}, author = {Maurizio Dusi and Saverio Niccolini and Antonio Barbuzzi and M. Milanesio and Alessandro Finamore and Brian Trammell and Edion Tego and Francesco Matera and Tivadar Szemethy and Rolf Winter and Zied Ben-Houidi and Andrea Fregosi and Benoit Donnet and Fabrizio Invernizzi and Dimitri Papadimitriou and Ilias Leontiadis and Yan Grunenberger and P. Casas} } @inproceedings {Aru2013, title = {Quality-of-Experience driven Acceleration of Thin Client Connections}, booktitle = {IEEE International Symposium on Network Computing and Applications}, year = {2013}, month = {08/2013}, edition = {12}, doi = {10.1109/NCA.2013.26}, author = {Mayutan Arumaithurai and Jan Seedorf and Maurizio Dusi and Edo Monticelli and Renato Lo Cigno} } @inproceedings {Det2013, title = {Revealing Middlebox Interference with Tracebox}, booktitle = {ACM/USENIX Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, abstract = {

Middleboxes such as firewalls, NAT, proxies, or Deep Pack-et Inspection play an\ increasingly important role in various types of IP networks, including\ enterprise and cellular networks. Recent studies have shed the light on their\ impact on real traffic and the complexity of managing them. Network operators\ and researchers have few tools to understand the impact of those boxes on any
path. In this paper, we propose tracebox, an extension to the widely used\ traceroute tool, that is capable of detecting various types of middlebox\ interference over almost any path. \ tracebox sends IP packets containing TCP\ segments with different TTL values and analyses the packet encapsulated in the\ returned ICMP messages. Further, as recent routers quote, in the ICMP message,\ the entire IP packet that they received, tracebox is able to detect any\ modification performed by upstream middleboxes. In addition, tracebox can often\ pinpoint the network hop where the middlebox interference occurs. We evaluate\ tracebox with measurements performed on PlanetLab nodes. Our analysis reveals\ various types of middleboxes that were not expected on such an experimental\ testbed supposed to be connected to the Internet without any restriction.

}, keywords = {middlebox, network discovery, tracebox}, doi = {10.1145/2504730.2504757}, author = {Gregory Detal and Benjamin Hesmans and Olivier Bonaventure and Yves Vanaubel and Benoit Donnet} } @article {Pap2013c, title = {Selection of Existing Probes and Datasets}, number = {D2.1}, year = {2013}, month = {08/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, abstract = {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{\textquoteright}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}, keywords = {active probes, existing probes, passive probes, probes, proxy probes}, author = {Dimitri Papadimitriou and Dario Rossi and YiXi Gong and Brian Trammell and Marco Milanesio and Ernst Biersack and Rolf Winter and Francesco Matera and Maurizio Dusi and Balazs Szabo and Tivadar Szemethy and Alessandro Finamore and Marco Mellia and Alessandro Capello and Fabio Invernizzi and Omar Jabr and Ilias Leontiadis and Benoit Donnet} } @article {Ros2013a, title = {Specification of mPlane Access Control and Data Protection Mechanisms}, number = {D1.2}, year = {2013}, month = {08/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, abstract = {

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{\textquoteright} 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{\textquoteright} 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.

}, keywords = {access control, anonymisation, authentication plane, privacy, security}, author = {Gianni De Rosa and Stefano Pentassuglia} } @article {Dav2013, title = {Stream-monitoring with blockmon: convergence of network measurements and data analytics platforms}, journal = {SIGCOMM Comput. Commun. Rev.}, volume = {43}, year = {2013}, pages = {29{\textendash}36}, keywords = {data analysis, distributed computing, performance analysis}, issn = {0146-4833}, doi = {10.1145/2479957.2479962}, url = {http://doi.acm.org/10.1145/2479957.2479962}, author = {Simoncelli, Davide and Maurizio Dusi and Francesco Gringoli and Saverio Niccolini} } @article {Tra2013a, title = {Use Case Elaboration and Requirements Specification}, number = {D1.1}, year = {2013}, month = {01/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, abstract = {

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{\textquoteright}s experience.\ 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{\textquoteright}s integrated trial.\ 

}, keywords = {architecture, measurement, platform, scenario, use case}, issn = {D1.1}, author = {Brian Trammell and Stephan Neuhaus and Francesco Matera and Ernst Biersack and Antonio Barbuzzi and Saverio Niccolini and Mohamed Ahmed and Maurizio Dusi and Tivadar Szemethy and Balazs Szabo and P. Casas and A B{\"a}r and Konstantina Papagiannaki and Yan Grunenberger and Ilias Leontiadis and Rolf Winter and Zied Ben-Houidi and Giovanna Carofiglio and Samir Ghamri-Doudane and Diego Perino and D Rossi} } @inproceedings {Dra2012, title = {Inside Dropbox: Understanding Personal Cloud Storage Services}, booktitle = {Internet Measurement Conference - IMC}, year = {2012}, month = {11/2012}, publisher = {ACM}, organization = {ACM}, address = {Boston, MA}, abstract = {

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.

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.

All measurements used in our analyses are publicly avail- able in anonymized form at the SimpleWeb trace repository: http://traces.simpleweb.org/dropbox/

}, keywords = {Dropbox, passive measurement}, issn = {978-1-4503-1705-4}, doi = {10.1145/2398776.2398827}, url = {http://dl.acm.org/citation.cfm?id=2398776.2398827\&coll=DL\&dl=GUIDE\&CFID=225051145\&CFTOKEN=42401286}, author = {Idilio Drago and Marco Mellia and Maurizio M Munafo{\textquoteright} and Anna Sperotto and Ramin Sadre and Aiko Pras} }