@article {7096995, title = {Personal Cloud Storage Benchmarks and Comparison}, journal = {Cloud Computing, IEEE Transactions on}, volume = {PP}, year = {2015}, pages = {1-1}, abstract = {The large amount of space offered by personal cloud storage services (e.g., Dropbox and OneDrive), together with the possibility of synchronizing devices seamlessly, keep attracting customers to the cloud. Despite the high public interest, little information about system design and actual implications on performance is available when selecting a cloud storage service. Systematic benchmarks to assist in comparing services and understanding the effects of design choices are still lacking. This paper proposes a methodology to understand and benchmark personal cloud storage services. Our methodology unveils their architecture and capabilities. Moreover, by means of repeatable and customizable tests, it allows the measurement of performance metrics under different workloads. The effectiveness of the methodology is shown in a case study in which 11 services are compared under the same conditions. Our case study reveals interesting differences in design choices. Their implications are assessed in a series of benchmarks. Results show no clear winner, with all services having potential for improving performance. In some scenarios, the synchronization of the same files can take 20 times longer. In other cases, we observe a wastage of twice as much network capacity, questioning the design of some services. Our methodology and results are thus useful both as benchmarks and as guidelines for system design.}, keywords = {Benchmark testing, Cloud computing, Cloud storage, Computers, Google, Measurements, Performance, Servers, Synchronization}, issn = {2168-7161}, doi = {10.1109/TCC.2015.2427191}, author = {Enrico Bocchi and Idilio Drago and Marco Mellia} } @inproceedings {Boc2015, title = {Personal Cloud Storage: Usage, Performance and Impact of Terminals }, booktitle = {4th IEEE International Conference on Cloud Networking (IEEE CloudNet 2015)}, year = {2015}, month = {10/2015}, publisher = {IEEE}, organization = {IEEE}, address = {Niagara Falls, Canada}, abstract = {

Personal cloud storage services such as Dropbox and OneDrive are popular among Internet users. They help in sharing content and backing up data by relying on the cloud to store files. The rise of mobile terminals and the presence of new providers question whether the usage of cloud storage is evolving. This knowledge is essential to understand the workload these services need to handle, their performance, and implications. In this paper we present a comprehensive characterization of personal cloud storage services. Relying on traces collected for one month in an operational network, we show that users of each service present distinct behaviors. Dropbox is now threatened by competitors, with OneDrive and Google Drive reaching large market shares. However, the popularity of the latter services seems to be driven by their integration into Windows and Android. Indeed, around 50\% of their users do not produce any workload. Considering performance, providers show distinct trade-offs, with bottlenecks that hardly allow users to fully exploit their access line bandwidth. Finally, usage of cloud services is now ordinary among mobile users, thanks to the automatic backup of pictures and media files.

}, keywords = {Cloud storage, Monitoring}, url = {http://www.ieee-cloudnet.org/program.html}, author = {Enrico Bocchi and Idilio Drago and Marco Mellia} } @inproceedings {DR:TMA-14c, title = {Peeking Through the BitTorrent Seedbox Hosting Ecosystem}, booktitle = {Traffic Monitoring and Analysis (TMA)}, year = {2014}, abstract = {

In this paper, we propose a lightweight method for detecting and classifying BitTorrent content providers with a minimal amount of resources. While
heavy methodologies are typically used (which require long term observation
and data exchange with peers of the swarm and/or a semantic analysis of torrent
websites), we instead argue that such complexity can be avoided by analyzing
the correlations between peers and torrents. We apply our methodology to study
over 50K torrents injected in ThePirateBay during one month, collecting more
than 400K IPs addresses. Shortly, we find that exploiting the correlations not
only enhances the classification accuracy keeping the technique lightweight (our
methodology reliably identifies about 150 seedboxes), but also uncovers seeding behaviors that were not previously noticed (e.g., as multi-port and multi-host
seeding). Finally, we correlate the popularity of seedbox hosting in our dataset
to criteria (e.g., cost, storage space, Web popularity) that can bias the selection
process of BitTorrent content providers.

}, url = {http://www.enst.fr/~drossi/paper/rossi14tma-c.pdf}, author = {Dario Rossi and Guilhem Pujol and Xiao Wang and Fabien Mathieu} } @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} } @article {Pap2014, title = {Practical issues for the implementation of survivability and recovery techniques in optical networks}, journal = {Journal Optical Switching and Networking}, volume = {14}, year = {2014}, chapter = {179}, author = {Dimitri Papadimitriou}, editor = {G.Ellinas and J.Rak and D.Staessens and J.Sterbenz and K.Walkowiak} } @article {2014, title = {Practical issues for the implementation of survivability and recovery techniques in optical networks,}, journal = {Journal Optical Switching and Networking}, volume = {14}, year = {2014}, chapter = {179}, author = {Dimitri Papadimitriou} } @inproceedings {Chi2013, title = {Passive bufferbloat measurement exploiting transport layer information}, booktitle = {IEEE GLOBECOM}, year = {2013}, month = {12/2013}, url = {http://www.enst.fr/~drossi/paper/rossi13globecom.pdf}, author = {C. Chirichella and D Rossi and C. Testa and T. Friedman and A. Pescape} } @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} } @article {Tra2013b, title = {python-ipfix-0.9.1}, year = {2013}, abstract = {

This module provides a Python interface to IPFIX message streams, and provides tools for building IPFIX Exporting and Collecting Processes. It handles message framing and deframing, encoding and decoding IPFIX data records using templates, and a bridge between IPFIX ADTs and appropriate Python data types.\ 

}, url = {http://pypi.python.org/pypi/ipfix}, author = {Brian Trammell} }