<?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%">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>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></records></xml>