@inproceedings {DR:AIMS-15, title = {Anycast census and geolocation}, booktitle = {7th Workshop on Active Internet Measurements (AIMS 2015)}, year = {2015}, month = {April 2015}, url = {http://www.enst.fr/~drossi/paper/rossi15aims.pdf}, author = {Cicalese, Danilo and Auge, Jordan and Joumblatt, Diana and Rossi, Dario and Friedman, Timur} } @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} } @inproceedings {DR:INFOCOM-15a, title = {A Fistful of Pings: Accurate and Lightweight Anycast Enumeration and Geolocation}, booktitle = {IEEE INFOCOM}, year = {2015}, month = {04/2015}, abstract = {

Use of IP-layer anycast has increased in the last few years: once relegated to DNS root and top-level domain servers, anycast is now commonly used to assist distribution of general purpose content by CDN providers. Yet, the measurement techniques for discovering anycast replicas have been designed around DNS, limiting their usefulness to this particular service. This raises the need for protocol agnostic methodologies, that should additionally be as lightweight as possible in order to scale up anycast service discovery. This is precisely the aim of this paper, which proposes a new method for exhaustive and accurate enumeration and city-level geolocation of anycast instances, requiring only a handful of latency measurements from a set of known vantage points. Our method exploits an iterative workflow that enumerates (an optimization problem) and geolocates (a classification problem) anycast replicas. We thoroughly validate our methodology on available ground truth (several DNS root servers), using multiple measurement infrastructures (PlanetLab, RIPE), obtaining extremely accurate results (even with simple algorithms, that we compare with the global optimum), that we make available to the scientific community. Compared to the state of the art work that appeared in INFOCOM 2013 and IMC 2013, our technique (i) is not bound to a specific protocol, (ii) requires 1000 times fewer vantage points, not only (iii) achieves over 50\% recall but also (iv) accurately identifies the city-level geolocation for over 78\% of the enumerated servers, with (v) a mean geolocation error of 361 km for all enumerated servers.

}, url = {http://www.enst.fr/~drossi/paper/rossi15infocom.pdf}, author = {Cicalese, Danilo and Joumblatt, Diana and Rossi, Dario and Buob, Marc-Olivier and Auge, Jordan and Friedman, Timur} } @inproceedings {DR:INFOCOM-15b, title = {A Lightweight Anycast Enumeration and Geolocation}, booktitle = {IEEE INFOCOM, Demo Session}, year = {2015}, address = {Hong Kong, China}, abstract = {

Several Internet services such as CDNs, DNS name servers, and sinkholes use IP-layer anycast to reduce user response times and increase robustness with respect to network failures and denial of service attacks. However, current geolocation tools fail with anycast IP addresses. In our recent work [1], we remedy to this by developing an anycast detection, enumeration, and geolocation technique based on a set of delay measurements from a handful of geographically distributed vantage points. The technique (i) detects if an IP is anycast, (ii) enumerates replicas by finding the maximum set of non-overlapping disks (i.e., areas centered around vantage points), and (iii) geolocates the replicas by solving a classification problem and assigning the server location to the most likely city. We propose to demo this technique. In particular, we visually show how to detect an anycast IP, enumerate its replicas, and geolocate them on a map. The demo allows to browse previously geolocated services, as well as to explore new targets on demand.

}, url = {http://www.enst.fr/~drossi/paper/rossi15infocom-b.pdf}, author = {Cicalese, Danilo and Joumblatt, Diana and Rossi, Dario and Buob, Marc-Olivier and Auge, Jordan and Friedman, Timur} } @inproceedings {Kut2015, title = {Weighted Similarity Estimation in Data Streams}, booktitle = {CIKM}, year = {2015}, month = {10/2015}, publisher = {ACM}, organization = {ACM}, abstract = {

Similarity computation between pairs of objects is often a bottleneck in many applications that have to deal with massive volumes of data. Motivated by applications such as collaborative filtering in large-scale recommender systems, and influence probabilities learning in social networks, we present new randomized algorithms for the estimation of weighted similarity in data streams.

Previous works have addressed the problem of learning binary similarity measures in a streaming setting. To the best of our knowledge, the algorithms proposed here are the first that specifically address the estimation of weighted similarity in data streams. The algorithms need only one pass over the data, making them ideally suited to handling massive data streams in real time.

We obtain precise theoretical bounds on the approximation error and complexity of the algorithms. The results of evaluating our algorithms on two real-life datasets validate the theoretical findings and demonstrate the applicability of the proposed algorithms.

}, author = {Konstantin Kutzkov and Mohamed Ahmed and Sofia Nikitaki} } @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} } @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 {Cas2014a, title = {Distributed active measurement of Internet queuing delays}, booktitle = {Passive and Active Measurement (PAM), Extended Abstract}, year = {2014}, month = {March}, address = {Los Angeles, USA}, abstract = {

Despite growing link capacities, over-dimensioned buffers are still causing, in the Internet of the second decade of the third millenium, hosts to suffer from severe queuing delays (or bufferbloat). While maximum bufferbloat possibly exceeds few seconds, it is far less clear how often this maximum is hit in practice. This paper reports on our ongoing work to build a spatial and temporal map of Internet bufferbloat, describing a system based on distributed agents running on PlanetLab that aims at providing a quantitative answer to the above question.

}, url = {http://www.enst.fr/~drossi/paper/rossi14pam-b.pdf}, author = {P. Casoria and D Rossi and Jordan Aug{\'e} and Marc-Oliver Buob and T. Friedman and A. Pescape} } @inproceedings {DR:TRAC-14, title = {A per-Application Account of Bufferbloat: Causes and Impact on Users}, booktitle = {5th International Workshop on TRaffic Analysis and Characterization (TRAC), Best Paper Award}, year = {2014}, abstract = {

We propose a methodology to gauge the extent of queueing delay (aka bufferbloat) in the Internet, based on purely passive measurement of TCP traffic. We implement our methodology in Tstat and make it available as open source software. We leverage Deep Packet Inspection (DPI) and behavioral classification of Tstat to breakdown the queueing delay across different applications, in order to evaluate the impact of bufferbloat on user experience. We show that there is no correlation between the ISP traffic load and the queueing delay, thus confirming that bufferbloat is related only to the traffic of each single user (or household). Finally, we use frequent itemset mining techniques to associate the amount of queueing delay seen by each host with the set of its active applications, with the goal of investigating the root cause of bufferbloat.

}, url = {http://www.enst.fr/drossi/paper/rossi14trac.pdf}, author = {Andrea Araldo and Dario Rossi} } @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} } @article {rfc7125, title = {Revision of the tcpControlBits IP Flow Information Export (IPFIX) Information Element (RFC 7125)}, year = {2014}, month = {02/2014}, abstract = {
This document revises the tcpControlBits IP Flow Information Export (IPFIX) Information Element as originally defined in RFC 5102 to reflect changes to the TCP Flags header field since RFC 793.
}, url = {http://www.ietf.org/rfc/rfc7125.txt}, author = {B. Trammell and P. Aitken} } @inproceedings {DR:PAM-14c, title = {Violation of Interdomain Routing Assumptions}, booktitle = {Passive and Active Measurement (PAM)}, year = {2014}, month = {03/2014}, address = {Los Angeles, USA}, url = {http://www.enst.fr/~drossi/paper/rossi14pam-c.pdf}, author = {R. Mazloum and M.-O. Buob and J. Auge and B. Baynat and T. Friedman and D. Rossi} } @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 {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} } @inproceedings {Ara2013, title = {Dissecting Bufferbloat: Measurement and Per-Application Breakdown of Queueing Delay}, booktitle = {ACM CoNEXT{\textquoteright}13, Student Workshop}, year = {2013}, abstract = {

We propose a passive methodology to estimate the queueing delay incurred by TCP traffic, and additionally leverage DPI classification to breakdown the delay across different applications. Ultimately, we correlate the queueing delay to the performance perceived by the users of that applications, depending on their delay-sensitivity. We implement our methodology in Tstat, and make it available 1 as open source software to the community. We validate and tune the tool, and run a preliminary measurement campaign based on a real ISP traffic trace, showing interesting yet partly counter-intuitive results.

}, doi = {10.1145/2537148.2537785}, url = {http://www.enst.fr/~drossi/paper/rossi13conext.pdf}, author = {A. Araldo and D Rossi} } @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} } @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 {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 {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} } @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 {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} }