Measuring web feature impacts in BitTorrent-like systems

  • Authors:
  • Sirui Yang;Hai Jin;Bo Li;Xiaofei Liao;Hong Yao;Qi Huang

  • Affiliations:
  • Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China

  • Venue:
  • Proceedings of the 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness
  • Year:
  • 2008

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Abstract

In Peer-to-Peer (P2P) file sharing systems, the attributes of resource description can influence the user behavior, especially on resource selection. However, this has been only qualitatively speculated but lacks of quantitative analysis. In this paper, we carry out a systematically quantitative study on the impact of these attributes presented in the form of web features, by measuring the largest BitTorrent website in CERNET. The measurement lasts for 31 days, and there are 168,610 records containing 11,228 distinct resources collected. The result is two-fold. On one hand, it confirms the above qualitative speculation; on the other hand, it shows more significant findings: (1) with the highlight feature on popular items, the downloads of each resource yield to a long-tail distribution however deviating from Zipf Law; (2) publications with attracting titles disseminate 1.9 times faster than others; (3) publisher authority feature does not evidently help the system escaping from malicious resources' pervasion; (4) other features such as taxonomy and size also influence users' choice. We further demonstrate the implications of the web feature impact for system designers and potential attackers.