Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Modeling and performance analysis of BitTorrent-like peer-to-peer networks
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Influences on cooperation in BitTorrent communities
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
Incentives in BitTorrent induce free riding
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
Measurements, analysis, and modeling of BitTorrent-like systems
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Modeling fetch-at-most-once behavior in peer-to-peer file-sharing systems
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
The bittorrent p2p file-sharing system: measurements and analysis
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
Power laws for monkeys typing randomly: the case of unequal probabilities
IEEE Transactions on Information Theory
An improved strategy of piece selection in P2P
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
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Logs of a BitTorrent (BT) site on campus are used to characterize the information sharing properties of BT users. The characteristics of (1) user’s publishing and downloading behaviors, (2) the life span of the torrent and (3) user’s downloaded, uploaded amount are addressed in the paper. Our main contributions are: (1) the distribution of users publishing characteristics has a flat head which is similar to that of user’s information fetch behaviors, but cannot be explained by the well-known fetch-at-most-once principle. An indirect selection model is proposed to explain the phenomenon. (2) The lifetime y of a torrent file is tightly correlated with user’s interests x (the number of fetches) (3) Distributions of user’s downloaded amount and uploaded amount are essentially different. Approximately the former is exponential but the latter is power-law. The Cobb-Douglas like utility (CDLU) function is applied to study the relationship between them and a simple bound is found in user’s CDLU.