Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/6275

VOVO: VCR-Oriented Video-on-Demand in Large-Scale Peer-to-Peer Networks

Authors He, Yuan
Liu, Yunhao
Issue Date 2009
Source IEEE transactions on parallel and distributed systems , v. 20, (4), 2009, APR, p. 528-539
Summary Most P2P Video-on-Demand (VOD) schemes focus more on mending service architectures and optimizing overlays but do not carefully consider the user behavior and the benefit of prefetching strategies. As a result, they cannot better support VCR-oriented services in terms of substantive asynchronous clients or free VCR controls for P2P VODs. To address this issue, we propose VOVO, a VCR-oriented VOD for large-scale P2P networks. By mining associations inside each video, the segments requested in VCR interactivities are predicted based on the information collected through gossips. Together with a hybrid caching strategy, a collaborative prefetching scheme is designed to optimize resource distribution among neighboring peers. We evaluate VOVO through extensive experiments. Results show that VOVO is scalable and effective, providing short start-up latencies and good performance in VCR interactivities.
Subjects
ISSN 1045-9219
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Language English
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