@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} } @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} } @inproceedings {7249283, title = {Lagrangian relaxation for the time-dependent combined network design and routing problem}, booktitle = {Communications (ICC), 2015 IEEE International Conference on}, year = {2015}, month = {June}, publisher = {IEEE XPlore}, organization = {IEEE XPlore}, address = {London, United-Kingdom}, keywords = {allocation planning process, flow conservation constraints, integer programming, integer programming methods, Lagrangian relaxation, linear programming, Maintenance engineering, multi-commodity capacitated fixed charge network design, network routing problem, Optimization, Quality of Service, Reliability, resource allocation, resource installation, Resource management, Routing, routing decision process, telecommunication network routing, telecommunication traffic, time-dependent combined network design, traffic demands}, doi = {10.1109/ICC.2015.7249283}, author = {Dimitri Papadimitriou and Bernard Fortz and Enrico Gorgone} } @inproceedings {Tra2015, title = {A New Transport Encapsulation for Middlebox Cooperation}, booktitle = {Proceedings of the 2015 IEEE Conference on Standards for Communications and Networking}, year = {2015}, month = {Oct}, address = {Tokyo, Japan}, author = {Brian Trammell and Mirja Kuehlewind and Elio Gubser and Joe Hildebrand} } @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 {Cas2015d, title = {Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field}, booktitle = {IRTF \& ISOC Workshop on Research and Applications of Internet Measurements (RAIM)}, year = {2015}, month = {11/2015}, author = {P Casas and B Gardlo and M Seufert and F Wamser and R Schatz} } @inproceedings {Cas2015c, title = {Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field}, booktitle = {11th International Conference on Network and Service Management (CNSM)}, year = {2015}, month = {10/2015}, author = {P Casas and B Gardlo and M Seufert and F Wamser and R Schatz} } @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 {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} } @inproceedings {Bae2014, title = {DBStream: an Online Aggregation, Filtering and Processing System for Network Traffic Monitoring}, booktitle = {TRAC}, year = {2014}, month = {08/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Nicosia, Cyprus}, author = {Arian Baer and Pedro Casas and Lukasz Golab and Alessandro Finamore} } @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} } @article {DR:COMNET-14b, title = {{Fighting the bufferbloat: on the coexistence of AQM and low priority congestion control (extended version)}}, journal = {Elsevier Computer Networks}, volume = {60}, year = {2014}, chapter = {115--128}, abstract = {

Nowadays, due to excessive queuing, delays on the Internet can grow longer than the round trip time between the Moon and the Earth {\textendash} for which the {\textquoteleft}{\textquoteleft}bufferbloa t{\textquoteright}{\textquoteright} term was recently coined. Some point to active queue management (AQM) as the solution. Others propose end-to-end low-priority congestion control techniques (LPCC). Under both approaches, promising advances have been made in recent times: notable examples are CoDel for AQM, and LEDBAT for LPCC. In this paper, we warn of a potentially fateful interaction when AQM and LPCC techniques are combined: namely, AQM resets the relative level of priority between best-effort and low-priority congestion control protocols. We validate the generality of our findings by an extended set of experiments with packet-level ns2 simulation, considering 5 AQM techniques and 3 LPCC protocols, and carry on a thorough sensitivity analysis varying several parameters of the networking scenario. We complete the simulation via an experimental campaign conducted on both controlled testbeds and on the Internet, confirming the reprioritization issue to hold in the real world at least under all combination of AQM policies and LPCC protocols available in the Linux kernel. To promote cross-comparison, we make our scripts and dataset available to the research community.

}, url = {http://www.enst.fr/~drossi/paper/rossi14comnet-b.pdf}, author = {YiXi Gong and Dario Rossi and Claudio Testa and Silvio Valenti and Dave Taht} } @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 {Ben2014, title = {Gold mining in a River of Internet Content Traffic}, booktitle = {6th International Workshop on Traffic Monitoring and Analysis, TMA}, year = {2014}, month = {04/2014}, publisher = {Springer}, organization = {Springer}, address = {London}, abstract = {With the advent of Over-The-Top content providers (OTTs), Internet Service Providers (ISPs) saw their portfolio of services shrink to the low margin role of data transporters. In order to counter this effect, some ISPs started to follow big OTTs like Facebook and Google in trying to turn their data into a valuable asset. In this paper, we explore the questions of what meaningful information can be extracted from network data, and what interesting insights it can provide. To this end, we tackle the first challenge of detecting {\textquotedblleft}user-URLs{\textquotedblright}, i.e., those links that were clicked by users as opposed to those objects automatically downloaded by browsers and applications. We devise algorithms to pinpoint such URLs, and validate them on manually collected ground truth traces. We then apply them on a three-day long traffic trace spanning more than 19,000 residential users that generated around 190 million HTTP transactions. We find that only 1.6\% of these observed URLs were actually clicked by users. As a first application for our methods, we answer the question of which platforms participate most in promoting the Internet content. Surprisingly, we find that, despite its notoriety, only 11\% of the user URL visits are coming from Google Search. }, keywords = {Content mining, HTTP Traffic, URL extraction}, author = {Zied Ben-Houidi and Giuseppe Scavo and Samir Ghamri-Doudane and Alessandro Finamore and Stefano Traverso and Marco Mellia} } @inproceedings {Tra2014, title = {Inline Data Integrity Signals for Passive Measurement}, booktitle = {Sixth International Workshop on Traffic Monitoring and Analysis (TMA 2014)}, year = {2014}, month = {04/2014}, abstract = {

In passive network measurement, the quality of an observed traffic stream is obviously crucial to the quality of the results. Some sources of error (e.g., packet loss at a capture device) are well understood, others less so. In this work, we describe the inline data integrity measurement provided by the QoF TCP-aware flow meter. By instrumenting the data structures QoF uses for detecting lost and retransmitted TCP segments, we can provide an in-band, per-flow estimate of observation loss: segments which were received by the recipient but not observed by the flow meter. We evaluate this mechanism against controlled, induced error, and apply it to two data sets used in previous work.

}, author = {Brian Trammell and David Gugelmann and Nevil Brownlee} } @inproceedings {Bae2014a, title = {Large-Scale Network Traffic Monitoring with DBStream, a System for Rolling Big Data Analysis}, booktitle = {International Conference on Big Data, IEEE BigData}, year = {2014}, month = {11/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Washington D.C., USA}, abstract = {

The complexity of the Internet has rapidly increased, making it more important and challenging to design scalable network monitoring tools. Network monitoring typically requires rolling data analysis, i.e., continuously and incrementally updating (rolling-over) various reports and statistics over high-volume data streams. In this paper, we describe DBStream, which is an SQL-based system that explicitly supports incremental queries for rolling data analysis. We also present a performance comparison of DBStream with a parallel data processing engine (Spark), showing that, in some scenarios, a single DBStream node can outperform a cluster of ten Spark nodes on rolling network monitoring workloads. Although our performance evaluation is based on network monitoring data, our results can be generalized to other big data problems with high volume and velocity.

}, keywords = {Big Data Analysis, Data Stream Processing, network data analysis, System Performance}, author = {Arian B{\"a}r and Alessandro Finamore and Pedro Casas and Lukasz Golab and Marco Mellia} } @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} } @article {grimaudoTNSM2014, title = {SeLeCT: Self-Learning Classifier for Internet Traffic}, journal = {IEEE Transactions on Network and Service Management}, volume = {11}, year = {2014}, month = {06/2014}, chapter = {144}, abstract = {

Network visibility is a critical part of traffic engineering, network management, and security. The most popular\ current solutions - Deep Packet Inspection (DPI) and statistical\ classification, deeply rely on the availability of a training set.\ Besides the cumbersome need to regularly update the signatures,\ their visibility is limited to classes the classifier has been trained\ for. Unsupervised algorithms have been envisioned as a viable\ alternative to automatically identify classes of traffic. However,\ the accuracy achieved so far does not allow to use them for traffic\ classification in practical scenario.

To address the above issues, we propose SeLeCT, a Self-Learning Classifier for Internet Traffic. It uses unsupervised algorithms along with an adaptive seeding approach to automatically\ let classes of traffic emerge, being identified and labeled. Unlike\ traditional classifiers, it requires neither a-priori knowledge of\ signatures nor a training set to extract the signatures. Instead,\ SeLeCT automatically groups flows into pure (or homogeneous)\ clusters using simple statistical features. SeLeCT simplifies label\ assignment (which is still based on some manual intervention) so\ that proper class labels can be easily discovered. Furthermore,\ SeLeCT uses an iterative seeding approach to boost its ability to\ cope with new protocols and applications.

We evaluate the performance of SeLeCT using traffic traces\ collected in different years from various ISPs located in 3\ different continents. Our experiments show that SeLeCT achieves\ excellent precision and recall, with overall accuracy close to 98\%.\ Unlike state-of-art classifiers, the biggest advantage of SeLeCT\ is its ability to discover new protocols and applications in an\ almost automated fashion.

}, keywords = {clustering, self-seeding, Traffic Classification, unsupervised machine learning}, author = {Luigi Grimaudo and Marco Mellia and Elena Baralis and Ram Keralapura} } @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} } @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} } @inproceedings {Gon2013, title = {Fighting the bufferbloat: on the coexistence of AQM and low priority congestion control}, booktitle = {IEEE INFOCOM Workshop on Traffic Monitoring and Analysis (TMA{\textquoteright}13)}, year = {2013}, keywords = {Bufferbloat}, doi = {10.1109/INFCOM.2013.6567153}, url = {http://www.enst.fr/~drossi/paper/rossi13tma-b.pdf}, author = {YiXi Gong and D Rossi and C. Testa and S. Valenti and D. Taht} } @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 {Gon2013a, title = {Modeling the interdependency of low-priority congestion control and active queue management}, booktitle = { 25th International Teletraffic Congress (ITC{\textquoteright}25), Runner up for best-paper award}, year = {2013}, abstract = {

Recently, a negative interplay has been shown to
arise when scheduling/AQM techniques and low-priority conges-
tion control protocols are used together: namely, AQM resets
the relative level of priority among congestion control protocols.
This work explores this issue by (i) studying a fluid model that
describes system dynamics of heterogeneous congestion control
protocols competing on a bottleneck link governed by AQM and
(ii) proposing a system level solution able to reinstate priorities
among protocols.

}, doi = {10.1109/ITC.2013.6662942}, author = {YiXi Gong and D Rossi and Emilio Leonardi} } @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 {Val2013, title = {RILAnalyzer: a Comprehensive 3G Monitor on Your Phone}, booktitle = {Internet Measurement Conference (IMC)}, year = {2013}, doi = {10.1145/2504730.2504764}, author = {Narseo Vallina-Rodriguez and A. Aucinas and M. Almeida and Yan Grunenberger and Konstantina Papagiannaki and Jon Crowcroft} } @inproceedings {Api2013, title = {SEARUM: a cloud-based SErvice for Association RUle Mining}, booktitle = {The 11th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA-13)}, year = {2013}, abstract = {

Large volumes of data are being produced by various modern applications at an ever increasing rate. These applications range from wireless sensors networks to social networks. The automatic analysis of such huge data volume is a challenging task since a large amount of interesting knowledge can be extracted. Association rule mining is an exploratory data analysis method able to discover interesting and hidden correlations among data. Since this data mining process is characterized by computationally intensive tasks, efficient distributed approaches are needed to increase its scalability. This paper proposes a novel cloud-based service, named SEARUM, to efficiently mine association rules on a distributed computing model. SEARUM consists of a series of distributed MapReduce jobs run in the cloud. Each job performs a different step in the association rule mining process. As a case study, the proposed approach has been applied to the network data scenario. The experimental validation, performed on two real network datasets, shows the effectiveness and the efficiency of\ SEARUM in mining association rules on a distributed computing model.

}, keywords = {association rule mining, cloud-based service, distributed computing model, network data analysis}, doi = {10.1109/TrustCom.2013.153}, author = {Daniele Apiletti and Elena Baralis and Tania Cerquitelli and Silvia Chiusano and Luigi Grimaudo} } @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} } @inproceedings {Gri2013, title = {Self-Learning Classifier for Internet Traffic}, booktitle = {The 5th IEEE International Traffic Monitoring and Analysis Workshop (TMA 2013)}, year = {2013}, abstract = {

Network visibility is a critical part of traffic engineering, network management, and security. Recently, unsupervised algorithms have been envisioned as a viable alternative\ to automatically identify classes of traffic. However, the accuracy\ achieved so far does not allow to use them for traffic classification\ in practical scenario.
In this paper, we propose SeLeCT, a Self-Learning Classifier\ for Internet traffic. It uses unsupervised algorithms along with\ an adaptive learning approach to automatically let classes of\ traffic emerge, being identified and (easily) labeled. SeLeCT\ automatically groups flows into pure (or homogeneous) clusters\ using alternating simple clustering and filtering phases to remove\ outliers. SeLeCT uses an adaptive learning approach to boost its\ ability to spot new protocols and applications. Finally, SeLeCT\ also simplifies label assignment (which is still based on some\ manual intervention) so that proper class labels can be easily\ discovered.
We evaluate the performance of SeLeCT using traffic traces\ collected in different years from various ISPs located in 3\ different continents. Our experiments show that SeLeCT achieves\ overall accuracy close to 98\%. Unlike state-of-art classifiers, the\ biggest advantage of SeLeCT is its ability to help discovering\ new protocols and applications in an almost automated fashion.

}, doi = {10.1109/INFCOMW.2013.6562900}, author = {Luigi Grimaudo and Marco Mellia and Elena Baralis and Ram Keralapura} } @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 {Tra2013, title = {Temporal locality in today{\textquoteright}s content caching: why it matters and how to model it}, journal = {ACM SIGCOMM Computer Communication Review}, volume = {43}, year = {2013}, month = {10/2013}, chapter = {5}, abstract = {

The dimensioning of caching systems represents a difficult task in the design of infrastructures for content distribution in the current Internet. This paper addresses the problem of defining a realistic arrival process for the content requests generated by users, due its critical importance for both analytical and simulative evaluations of the performance of caching systems. First, with the aid of YouTube traces collected inside operational residential networks, we identify the characteristics of real traffic that need to be considered or can be safely neglected in order to accurately predict the performance of a cache. Second, we propose a new parsimonious traffic model, named the Shot Noise Model (SNM), that enables users to natively capture the dynamics of content popularity, whilst still being suf- ficiently simple to be employed effectively for both analytical and scalable simulative studies of caching systems. Finally, our results show that the SNM presents a much better solution to account for the temporal locality observed in real traffic compared to existing approaches.

}, doi = {10.1145/2541468.2541470}, author = {Stefano Traverso and Mohamed Ahmed and Michele Garetto and Paolo Giaccone and Emilio Leonardi and Saverio Niccolini} } @inproceedings {Ale2013, title = {Is There a Case for Mobile Phone Content Pre-staging?}, booktitle = {Proceedings of the Ninth ACM Conference on Emerging Networking Experiments and Technologies (Best Short Paper Award)}, year = {2013}, month = {12/2013}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {

Content caching is a fundamental building block of the Internet. Caches are widely deployed at network edges to improve performance for end-users, and to reduce load on web servers and the backbone network. Considering mobile 3G/4G networks, however, the bottleneck is at the access link, where bandwidth is shared among all mobile terminals. As such, per-user capacity cannot grow to cope with the traffic demand. Unfortunately, caching policies would not reduce the load on the wireless link which would have to carry multiple copies of the same object that is being downloaded by multiple mobile terminals sharing the same access link.

In this paper we investigate if it is worth to push the caching paradigm even farther. We hypothesize a system in which mobile terminals implement a local cache, where popular content can be pushed/pre-staged. This exploits the peculiar broadcast capability of the wireless channels to replicate content "for free" on all terminals, saving the cost of transmitting multiple copies of those popular objects. Relying on a large data set collected from a European mobile carrier, we analyse the content popularity characteristics of mobile traffic, and quantify the benefit that the push-to-mobile system would produce. We found that content pre-staging, by proactively and periodically broadcasting "bundles" of popular objects to devices, allows to both greatly i) improve users{\textquoteright} performance and ii) reduce up to 20\% (40\%) the downloaded volume (number of requests) in optimistic scenarios with a bundle of 100 MB. However, some technical constraints and content characteristics could question the actual gain such system would reach in practice.

}, keywords = {content pre-staging, mobile networks}, isbn = {978-1-4503-2101-3}, doi = {10.1145/2535372.2535414}, url = {http://doi.acm.org/10.1145/2535372.2535414}, author = {Finamore, Alessandro and Mellia, Marco and Gilani, Zafar and Papagiannaki, Konstantina and Erramilli, Vijay and Grunenberger, Yan} } @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 {Val2012, title = {Breaking for commercials: characterizing mobile advertising}, booktitle = {Proceedings of the 2012 ACM conference on Internet measurement conference}, year = {2012}, publisher = {ACM}, organization = {ACM}, address = {Boston, MA}, abstract = {

Mobile phones and tablets can be considered as the first incarnation of the post-PC era. Their explosive adoption rate has been driven by a number of factors, with the most signifcant influence being applications (apps) and app markets. Individuals and organizations are able to develop and publish apps, and the most popular form of monetization is mobile advertising.

The mobile advertisement (ad) ecosystem has been the target of prior research, but these works typically focused on a small set of apps or are from a user privacy perspective. In this work we make use of a unique, anonymized data set corresponding to one day of traffic for a major European mobile carrier with more than 3 million subscribers. We further take a principled approach to characterize mobile ad traffic along a number of dimensions, such as overall traffic, frequency, as well as possible implications in terms of en- ergy on a mobile device.

Our analysis demonstrates a number of inefficiencies in today{\textquoteright}s ad delivery. We discuss the benefits of well-known techniques, such as pre-fetching and caching, to limit the energy and network signalling overhead caused by current systems. A prototype im- plementation on Android devices demonstrates an improvement of 50\% in terms of energy consumption for offline ad-sponsored apps while limiting the amount of ad related traffic.\ 

}, keywords = {advertisement, caching, cellular, energy, smartphones, traffic}, isbn = {978-1-4503-1705-4}, doi = {10.1145/2398776.2398812}, url = {http://doi.acm.org/10.1145/2398776.2398812}, author = {Narseo Vallina-Rodriguez and Jay Shah and Alessandro Finamore and Yan Grunenberger and Konstantina Papagiannaki and Hamed Haddadi and Jon Crowcroft} } @inproceedings {Gon2012, title = {Interaction or Interference: can AQM and Low Priority Congestion Control Successfully Collaborate}, booktitle = {ACM CoNEXT, Extended Abstract}, year = {2012}, month = {12/2012}, abstract = {

Heterogeneity in the Internet ecosystem sometimes turns interaction into interference. Over the years, active queue management (AQM) and end-to-end low-priority congestion control (LPCC) have been proposed as alternative solutions to counter the persistently full buffer problem -- that recently became popular under the {\textquoteleft}{\textquoteleft}bufferbloat{\textquoteright}{\textquoteright} term. In this work, we point out the existence of a negative interplay among AQM and LPCC techniques. Intuitively, as AQM is designed to penalize the most aggressive flows it mainly hit best effort TCP: it follows that LPCC is not able to maintain its low priority, thus becoming as aggressive as TCP. By an extended set of simulation on various AQM policies and LPCC protocols, including the very recent CoDel AQM and LEDBAT LPCC proposals, we point out that this interference is quite universal and deserves further attention.

}, doi = {10.1145/2413247.2413263}, url = {http://www.enst.fr/drossi/paper/rossi12conext.pdf}, author = {YiXi Gong and D Rossi and C. Testa and S. Valenti and D. Taht} } @inproceedings {Fin2012, title = {The need for an intelligent measurement plane: The example of time-variant CDN policies}, booktitle = {Telecommunications Network Strategy and Planning Symposium (NETWORKS), 2012 XVth International }, year = {2012}, month = {10/2012}, pages = {1 - 6 }, abstract = {In this paper we characterize how web-based services are delivered by large organizations in today{\textquoteright}s Internet. Taking advantage oftwo week-long data sets separated in time by 10 months and reporting the web activity of more than 10,000 ADSL residential customers, we identify the services offered by large organizations like Google, Akamai and Amazon. We then compare theevolution of both policies used to serve requests, and the infrastructure they use to match the users{\textquoteright} demand. Results depict anovercrowded scenario in constant evolution. Big-players are more and more responsible for the majority of the volume and a plethora of other organizations offering similar or more specific services through different CDNs and traffic policies. Unfortunately, no standard tools and methodologies are available to capture and expose the hidden properties of this in constant evolution picture. A deeper understanding of such dynamics is however fundamental to improve the performance of current and future Internet. To this extend, we claim the need for a Internet-wide, standard, flexible and intelligent measurement plane to be added tothe current Internet infrastructure.}, keywords = {Facebook, Google, Monitoring, Organizations, Servers, Streaming media, Throughput}, issn = {978-1-4673-1390-2}, doi = {http://dx.doi.org/10.1109/NETWKS.2012.6381662}, author = {Alessandro Finamore and Vinicius Gehlen and Marco Mellia and Maurizio M Munafo{\textquoteright}} } @inproceedings {Rio2012, title = {Wire-speed statistical classification of network traffic on commodity hardware}, booktitle = {ACM Internet Measurement Conference (IMC)}, year = {2012}, month = {11/2012}, abstract = {

In this paper we present a software-based traffic classification engine running on commodity multi-core hardware, able to process in real-time aggregates of up to 14.2Mpps over a single 10Gbps interface -- i.e., the maximum possible packet rate over a 10Gbps Ethernet links given the minimum frame size of 64Bytes. This significant advance with respect to the current state of the art in terms of achieved classification rates are made possible by: (i) the use of an improved network driver, PacketShader, to efficiently move batches of packets from the NIC to the main CPU; (ii) the use of lightweight statistical classification techniques exploiting the size of the first few packets of every observed flow; (iii) a careful tuning of critical parameters of the hardware environment and the software application itself.

}, doi = {10.1145/2398776.2398784}, author = {Pedro Maria Santiago del Rio and D Rossi and Francesco Gringoli and Lorenzo Nava and Luca Salgarelli and Javier Aracil} }