@article {Cas2016, title = {Unveiling Network and Service Performance Degradation in the Wild with mPlane}, journal = {IEEE Communications Magazine - Network Testing Series}, year = {2016}, abstract = {

Unveiling network and service performance issues in complex and highly decentralized systems such as the Internet is a major challenge. Indeed, the Internet is based on decentralization and diversity. However, its distributed nature leads to operational brittleness and difficulty in identifying the root causes of performance degradation. In such a context, network measurements are a fundamental pillar to shed light and to unveil design and implementation defects. To tackle this fragmentation and visibility problem, we have recently conceived mPlane, a distributed measurement platform which runs, collects and analyses traffic measurements to study the operation and functioning of the Internet. In this paper, we show the potentiality of the mPlane approach to unveil network and service degradation issues in live, operational networks, involving both fixed-line and cellular networks. In particular, we combine active and passive measurements to troubleshoot problems in end-customer Internet access connections, or to automatically detect and diagnose anomalies in Internet-scale services (e.g., YouTube) which impact a large number of end-users.

}, author = {Pedro Casas and Pierdomenico Fiadino and Sarah Wassermann and Stefano Traverso and Alessandro D{\textquoteright}Alconzo and Edion Tego and Francesco Matera and Marco Mellia} } @article {D61, title = {Demonstration Plan}, number = {D6.1}, year = {2015}, month = {01/2015}, type = {Public Deliverable}, issn = {D6.1}, author = {Pedro Casas and Edion Tego and Francesco Matera and Maurizio Dusi and A. Bakay and Balazs Szabo and G. Rozsa and Stefano Traverso and Ilias Leontiadis and L. Baltrunas and Yan Grunenberger and Andrea Fregosi and A. Kahveci and Eike Kowallik and G. Mattellini and C. Meregalli and Stefano Raffaglio and M. Russo and Andrea Sannino and M. Scarpino} } @article {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} } @article {Ber2014, title = {A Distributed Architecture for the Monitoring of Clouds and CDNs: Applications to Amazon AWS}, journal = {IEEE Transactions on Network and Service Management}, volume = {In press}, year = {2014}, abstract = {

Clouds and CDNs are systems that tend to separate the content being requested by users from the physical servers capable of serving it. From the network point of view, monitoring and optimizing performance for the traffic they generate is a challenging task, given the same resource can be located in multiple places, which can in turn change at any time. The first step in understanding Cloud and CDN systems is thus the engineering of a monitoring platform. In this paper, we propose a novel solution which combines passive and active measurements, and whose workflow has been tailored to specifically characterize the traffic generated by Cloud and CDN infrastructures. We validate our platform by performing a longitudinal characterization of the very well known Cloud and CDN infrastructure provider Amazon Web Services (AWS). By observing the traffic generated by more than 50,000 Internet users of an Italian ISP, we explore the EC2, S3 and CloudFront AWS services, unveiling their infrastructure, the pervasiveness of web-services they host, and their traffic allocation policies as seen from our vantage points. Most importantly, we observe their evolution over a two- year long period. The solution provided in this paper can be of interest for i) developers aiming at building measurement tools for Cloud Infrastructure Providers, ii) developers interested in failure and anomaly detection systems, and iii) third-party SLA certificators who can design systems to independently monitor performance. At last, we believe the results about AWS presented in this paper are interesting as they are among the first to unveil properties of AWS as seen from the operator point of view.

}, keywords = {Amazon, AWS, CDNs, Clouds}, author = {Ignacio Bermudez and Stefano Traverso and Marco Mellia and Maurizio Munafo{\textquoteright}} } @inproceedings {Tra2014b, title = {Exploiting Hybrid Measurements for Network Troubleshooting}, booktitle = {IEEE Networks}, year = {2014}, month = {09/2014}, publisher = {IEEE}, organization = {IEEE}, address = {Funchal, PT}, abstract = {Network measurements are a fundamental pillar to understand network performance and perform root cause analysis in case of problems. Traditionally, either active or passive measurements are considered. While active measurements allow to know exactly the workload injected by the application into the network, the passive measurements can offer a more detailed view of transport and network layer impacts. In this paper, we present a hybrid approach in which active throughput measurements are regularly run while a passive measurement tool monitors the generated packets. This allows us to correlate the application layer measurements obtained by the active tool with the more detailed view offered by the passive monitor. The proposed methodology has been implemented following the mPlane reference architecture, tools have been installed in the Fastweb network, and we collect measurements for more than three months. We report then a subset of results that show the benefits obtained when correlating active and passive measurements. Among results, we pinpoint cases of congestion, of ADSL misconfiguration, and of modem issues that impair throughput obtained by the users.}, keywords = {Hybrid measurements, measurement analysis, WP2}, author = {Stefano Traverso and Edion Tego and Eike Kowallik and Stefano Raffaglio and Andrea Fregosi and Marco Mellia and Francesco Matera} } @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} } @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} } @inproceedings {Ber2013, title = {Exploring the Cloud from Passive Measurements: the Amazon AWS case}, booktitle = {The 32nd Annual IEEE International Conference on Computer Communications (INFOCOM{\textquoteright}2013)}, year = {2013}, address = {Turin, Italy}, abstract = {

Cloud Providers are nowadays the most popular way to quickly deploy new services on the Internet. Understanding mechanisms currently adopted in cloud design is fundamental to identify possible bottlenecks, to optimize performance, and to design more efficient platforms. This paper presents a characterization of Amazon{\textquoteright}s Web Services (AWS), the most prominent cloud provider that offers computing, storage, and content delivery platforms. Leveraging passive measurements collected from several vantage points in Italy for several months, we explore the EC2, S3 and CloudFront AWS services to unveil their infrastructure, the pervasiveness of content they host, and their traffic allocation policies. Measurements reveal that most of the content residing on EC2 and S3 is served by one single Amazon datacenter located in Virginia despite it appears to be the worst performing one for Italian users. This causes traffic to take long and expensive paths in the network. Since no automatic migration and load-balancing policies are offered by AWS among different locations, content is exposed to outages, as we were able to observe in our data. The CloudFront CDN, on the contrary, shows much better performance thanks to the effective cache selection policy that serves 98\% of the traffic from the nearest available cache. CloudFront exhibits also dynamic load-balancing policies, in contrast to the static allocation of instances on EC2 and S3. Information presented in this paper will be useful for developers aiming at entrusting AWS to deploy their contents, and for researchers willing to improve cloud design.

}, doi = {10.1109/INFCOM.2013.6566769}, author = {Ignacio Nicolas Bermudez and Stefano Traverso and Marco Mellia and Maurizio M Munafo{\textquoteright}} } @article {Tra2013d, title = {mPlane Architecture Specification}, number = {D1.3}, year = {2013}, month = {11/2013}, institution = {mPlane Consortium}, type = {Public Deliverable}, address = {Torino}, keywords = {architecture, measurement, platform, scenario, use case}, author = {Brian Trammell and Marco Mellia and Alessandro Finamore and Stefano Traverso and Tivadar Szemethy and Balazs Szabo and D Rossi and Benoit Donnet and Fabrizio Invernizzi and Dimitri Papadimitriou} } @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} }