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.
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Xiao, B., Yu, J., Shao, Z., Li, M. (2006). Distributed Proximity-Aware Peer Clustering in BitTorrent-Like Peer-to-Peer Networks. In: Sha, E., Han, SK., Xu, CZ., Kim, MH., Yang, L.T., Xiao, B. (eds) Embedded and Ubiquitous Computing. EUC 2006. Lecture Notes in Computer Science, vol 4096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11802167_39
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DOI: https://doi.org/10.1007/11802167_39
Publisher Name: Springer, Berlin, Heidelberg
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