Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64359
Title: Distributed proximity-aware peer clustering in BitTorrent-like peer-to-peer networks
Authors: Xiao, B 
Yu, JD
Shao, ZL 
Li, ML
Keywords: Proximity-aware
Clustered BitTorrent (CBT)
Peer-to-peer networks
Super-peerscalability
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), v. 4096, p. 375-384 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
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.
Description: International Conference on Embedded and Ubiquitous Computing (EUC 2006), Seoul, Korea, 1-4 Aug 2006
URI: http://hdl.handle.net/10397/64359
ISBN: 978-3-540-36679-9 (print)
978-3-540-36681-2 (online)
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/11802167_39
Appears in Collections:Conference Paper

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