Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Characterizing the query behavior in peer-to-peer file sharing systems
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Rarest first and choke algorithms are enough
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Understanding user behavior in large-scale video-on-demand systems
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
Measurements, analysis, and modeling of BitTorrent-like systems
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Traffic modeling and proportional partial caching for peer-to-peer systems
IEEE/ACM Transactions on Networking (TON)
Content availability and bundling in swarming systems
Proceedings of the 5th international conference on Emerging networking experiments and technologies
Power-law revisited: large scale measurement study of P2P content popularity
IPTPS'10 Proceedings of the 9th international conference on Peer-to-peer systems
Characterizing Web-Based Video Sharing Workloads
ACM Transactions on the Web (TWEB)
Unraveling the BitTorrent Ecosystem
IEEE Transactions on Parallel and Distributed Systems
The bittorrent p2p file-sharing system: measurements and analysis
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
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Workload characterization is important for understanding how systems and services are used in practice and to help identify design improvements. To better understand the longitudinal workload dynamics of chunk-based content delivery systems, this paper analyzes the BitTorrent usage as observed from two different vantage points. Using two simultaneously collected 48-week long traces, we analyze the differences in download characteristics and popularity dynamics observed locally at a university campus versus at a global scale. We find that campus users typically download larger files and are early adopters of new content, in the sense that they typically download files well before the time at which the global popularity of the files peak. The noticeable exception is music files, which the campus users are late to download. We also find that there typically is high churn in the set of files that are popular each week, both locally and globally, and that the most popular files peak significantly later than their release date. These findings provide insights that may improve the efficiency of content sharing locally, and thus increase the scalability of the global system.