Abstract
In recent years, the data-driven peer-to-peer streaming systems have been extensive deployed in Internet. In these systems, the transfer of media blocks among nodes involves two scheduling issues: each node should request the streaming blocks of interest from its peers (i.e. block request scheduling), on the other hand, it also should decide how to satisfy the requests received from its peers (i.e. block delivery scheduling) given its bandwidth limitations. Intuitively, these two scheduling issues are critical to the performance of data-driven streaming systems. However, most of the work in the literature focused on the block request scheduling issue, and very few concentrated on the latter. Consequently, the performance of the system may be affected seriously due to an unsophisticated scheduling strategy. In this paper, we analytically study the block delivery scheduling problem and model it as an optimization problem based on the satisfaction degrees of nodes and the playback performance of the system. We then propose a scheduling strategy and prove the optimality of the strategy to the optimization problem. Lastly, we illustrate the effectiveness of the proposed strategy by extensive simulation.
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© 2012 Springer-Verlag Berlin Heidelberg
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Huang, G., Chen, Z. (2012). A Optimal Scheduling Strategy for Data-Driven Peer-to-Peer Streaming. In: Lee, R. (eds) Computer and Information Science 2012. Studies in Computational Intelligence, vol 429. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30454-5_12
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DOI: https://doi.org/10.1007/978-3-642-30454-5_12
Publisher Name: Springer, Berlin, Heidelberg
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