Distributed proximity-aware peer clustering in BitTorrent-like peer-to-peer networks

Bin Xiao, J.D. Yu, Zili Shao, M.L. Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In this paper, we propose a hierarchical architecture for grouping peers into clusters in a large-scale BitTorrent-like underlying overlay network in such a way that clusters are evenly distributed and that the peers within are relatively close together. We achieve this by constructing the CBT (Clustered BitTorrent) system with two novel algorithms: a peer joining algorithm and a super-peer selection algorithm. Proximity and distribution are determined by the measurement of distances among peers. Performance evaluations demonstrate that the new architecture achieves better results than a randomly organized BitTorrent network, improving the system scalability and efficiency while retaining the robustness and incentives of original BitTorrent paradigm.
Original languageEnglish
Title of host publicationLecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics)
PublisherSpringer
Pages375-384
Number of pages10
ISBN (Electronic)9783540366812
ISBN (Print)9783540366799
DOIs
Publication statusPublished - 2006
EventInternational Conference on Embedded and Ubiquitous Computing [EUC] -
Duration: 1 Jan 2006 → …

Conference

ConferenceInternational Conference on Embedded and Ubiquitous Computing [EUC]
Period1/01/06 → …

Keywords

  • Proximity-aware
  • Clustered BitTorrent (CBT)
  • Peer-to-peer networks
  • Super-peerscalability

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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