
This dissertation, "Bandwidth Partition Strategies for Minimizing Peer-to-peer Multi-file Distribution Time" by Xiang, Meng, , was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author.<br> Abstract:<br> Peer-to-Peer (P2P) technology has been developed rapidly during the past few years. Due to its superiorities on robustness and scalability, P2P technology has been viewed as a promising networking technology and many studies have been done on how to improve P2P technology.<br> P2P file distribution, as a major application of P2P technology, has also been studied a lot. The amount of time required for all peers to get the file has been considered as a major optimization metric, which we refer as the file distribution time. Researchers have proposed protocols to minimize the file distribution time for different cases. However, most of the existing works are based on the single-file scenario. On the other hand, studies show that in a file sharing application, users may download multiple files at the same time. In this thesis, we analyze the file distribution time for the distribution of multiple files in both wired and wireless networks.<br> We develop explicit expressions for lower bound of time needed to distribute multiple files in a heterogeneous P2P fluid model. Unlike the single-file scenario, we demonstrate that the theoretical lower bound in multi-file scenario is not always achievable. With a comprehensive consideration of all the configurations, we develop algorithms to partition the bandwidth of all the peers for a particular file such that the file distribution time is optimal.<br> DOI: 10.5353/th_b5089996<br> Subjects:<br> P
Page Count:
0
Publication Date:
2017-01-26
ISBN-10:
1361000589
ISBN-13:
9781361000588
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