Pitfalls of re-sharing BitTorrent contents: The failure of daily pattern

Haiyang Wang, Xu Cheng, Feng Wang, Jiangchuan Liu, Ke Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Peer-to-peer file sharing systems, most notably Bit-Torrent (BT), have achieved tremendous success among Internet users. Recent studies suggest that the long-term relationships among BT peers can be explored to enhance the downloading performance; for example, the cooperation of peers to re-share old contents. However, whether such relationships can be built still remain unknown. In this paper, we take a first step towards the real-world applicability of the content re-sharing through a measurement based study. We find that 95% peers cannot even meet each other again in the BT networks; therefore, most peers can hardly be organized for further cooperation. This result is contradict to the conventional understanding based on the observed daily arrival pattern in peer-to-peer networks. To better understand this, we revisit the arrival of BT peers as well as their long-range dependence. We find that the peers' arrival patterns are highly diverse; only a limited number of peers have very clear self-similar and periodic daily arrival features (which we call them stable peers). The arrivals of other peers are, however, quite random with the clear absence of long-range dependence.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Peer-to-Peer Computing, P2P 2011 - Proceedings
Pages352-355
Number of pages4
DOIs
StatePublished - 2011
Event11th IEEE International Conference on Peer-to-Peer Computing, P2P'11 - Kyoto, Japan
Duration: Aug 31 2011Sep 2 2011

Publication series

Name2011 IEEE International Conference on Peer-to-Peer Computing, P2P 2011 - Proceedings

Other

Other11th IEEE International Conference on Peer-to-Peer Computing, P2P'11
Country/TerritoryJapan
CityKyoto
Period8/31/119/2/11

Keywords

  • BitTorrent
  • Long-term relationship
  • Self-similar

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