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P2Cast: peer-to-peer patching scheme for VoD service
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Bullet: high bandwidth data dissemination using an overlay mesh
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Measurement and analysis of a streaming-media workload
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SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
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ISM '08 Proceedings of the 2008 Tenth IEEE International Symposium on Multimedia
VOVO: VCR-Oriented Video-on-Demand in Large-Scale Peer-to-Peer Networks
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Kangaroo: video seeking in P2P systems
IPTPS'09 Proceedings of the 8th international conference on Peer-to-peer systems
The design of video segmentation-aided VCR support for P2P VoD systems
IEEE Transactions on Consumer Electronics
Efficient search and scheduling in P2P-based media-on-demand streaming service
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Challenges in supporting non-linear and non-continuous media access in P2P systems
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User interactions such as seeks and pauses are widely supported by existing Peer-to-Peer Video-on-Demand (P2P VoD) streaming systems. Their effect on the streaming system, however, has not been well studied. Seeks cause peers to skip part of the video, making them stay in the system for shorter time, and thus contribute less. On the other hand, only part of the video is downloaded due to seeks, reducing peers' demand from the system. It is unclear which factor dominates the effect of seeks on the streaming system. Pauses during playback, on one hand, allow peers to stay longer in the system and upload more content. When interleaved with seeks, however, long pauses may increase peers' demand unnecessarily as peers may download content that will eventually be skipped by subsequent forward seeks. The collective effect of seeks and pauses, together with the known random peer departure, is unintuitive and needs to be addressed properly so as to understand the effect of human factors on the streaming system performance. In this article, we develop an analytical model to both qualitatively and quantitatively study the effect of seeks and pauses on mesh-based P2P VoD streaming systems, in particular, the effect on the server cost. Our model can help in understanding how human factors such as seeks and pauses affect the streaming system performance, tuning a P2P VoD system towards better system performance and stability, and providing a framework for capacity planning.