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 language | English |
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Title of host publication | Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) |
Publisher | Springer |
Pages | 375-384 |
Number of pages | 10 |
ISBN (Electronic) | 9783540366812 |
ISBN (Print) | 9783540366799 |
DOIs | |
Publication status | Published - 2006 |
Event | International Conference on Embedded and Ubiquitous Computing [EUC] - Duration: 1 Jan 2006 → … |
Conference
Conference | International Conference on Embedded and Ubiquitous Computing [EUC] |
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Period | 1/01/06 → … |
Keywords
- Proximity-aware
- Clustered BitTorrent (CBT)
- Peer-to-peer networks
- Super-peerscalability
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science