@inproceedings {Bae2015, title = {Cache Oblivious Scheduling of Shared Workloads}, booktitle = {31st IEEE International Conference on Data Engineering (ICDE)}, year = {2015}, month = {05/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Seoul, Korea}, abstract = {

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.

}, author = {Arian B{\"a}r and Lukasz Golab and Stefan Ruehrup and Mirko Schiavone and Pedro Casas} } @inproceedings {Faat1510:Cautious, title = {A Cautious Look at Using Internet Standards-to-be in Research Work}, booktitle = {2015 IEEE Conference on Standards for Communications and Networking (CSCN) (CSCN{\textquoteright}15)}, year = {2015}, address = {Tokyo, Japan}, abstract = {

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.

}, keywords = {document lifecycle, ietf, RFCs}, author = {Michael Faath and Rolf Winter and Fabian Weisshaar} } @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} } @inproceedings {DR:CoNEXT-15, title = {Characterizing IPv4 Anycast Adoption and Deployment}, booktitle = {ACM CoNEXT}, year = {2015}, month = {12/2015}, publisher = {ACM}, organization = {ACM}, address = {Heidelberg, DE}, url = {http://www.enst.fr/~drossi/paper/rossi15conext.pdf}, author = {Cicalese, Danilo and Auge, Jordan and Joumblatt, Diana and Friedman, Tim ur and Rossi, Dario} } @article {Teg2015, title = {Comparison of TCP congestion control algorithms in data transfers on high RTT }, year = {2015}, type = {Poster}, author = {Edion Tego and Francesco Matera} } @inproceedings {Cas2014e, title = {Characterizing Microsoft Lync Online in Mobile Networks: a Quality of Experience Perspective}, booktitle = {3rd IEEE International Conference on Cloud Networking}, year = {2014}, month = {10/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Luxembourg, Luxembourg}, abstract = {

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.

}, keywords = {Audioconferencing, Cloud QoE, Distributed Data Center, Microsoft Lync Online, MOS, Remote Desktop Sharing, Telepresence, Videoconferencing}, author = {Pedro Casas and Andreas Sackl and Sebastian Egger and Raimund Schatz} } @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} } @inproceedings {Boc2014, title = {Cloud Storage Service Benchmarking: Methodologies and Experimentations}, booktitle = {3rd IEEE International Conference on Cloud Networking (IEEE CloudNet 2014)}, year = {2014}, month = {10/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Luxembourg}, abstract = {

Data storage is one of today{\textquoteright}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.

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.\ 

}, keywords = {Amazon S3, Benchmarking, Cloud storage, Performance measurement, Web services, Windows Azure}, author = {Enrico Bocchi and Marco Mellia and Sofiane Sarni} } @inproceedings {Nay2014, title = {The Cost of the {\textquotedblleft}S{\textquotedblright} in HTTPS}, booktitle = {ACM Conference on emerging Networking EXperiments and Technologies (CoNEXT)}, year = {2014}, month = {12/2014}, author = {David Naylor and Alessandro Finamore and Ilias Leontiadis and Yan Grunenberger and Marco Mellia and Kostantina Papagiannaki and Peter Steenkiste} } @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} }