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On Improving Network Locality in BitTorrent-Like Systems

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Abstract

The emerging Peer-to-Peer (P2P) model has become a very popular paradigm for developing Internet-scale systems. The BitTorrent is an example of P2P system for sharing resources, including files and documents. Owing to the peer does not have the capability of locality aware, it cannot differentiate its neighbors belong to which Internet Service Provider (ISP), file sharing results in a large number of cross-ISP traffic (about 70%). ISPs often control BitTorrent traffic by bandwidth limiting for reducing cross-ISP traffic. In this paper, we propose an adaptive peer collaboration strategy to reduce cross-ISP traffic without additional equipment and backup mechanism, which means decreasing the cost of additional equipment. Internal peers can collaborate indirectly. In peer collaboration strategy, a peer chooses most of its neighbors from internal ISP as itself, and only a few from external ISPs for reducing transfer of cross-ISP by biased neighbor selection. Second, in order to decrease redundancy, we employ Advanced Tracker (AT) to record the information of pieces that owned by each ISP. Finally, we adopt dynamic priority allocation for improving the file download time. Experimental results show that our peer collaboration strategy outperforms previous approaches, decreases redundancy and decreases the file download time remarkably.

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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Ching, YC., Hsu, CH., Li, KC. (2009). On Improving Network Locality in BitTorrent-Like Systems. In: Mueller, P., Cao, JN., Wang, CL. (eds) Scalable Information Systems. INFOSCALE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10485-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-10485-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10484-8

  • Online ISBN: 978-3-642-10485-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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