Optimizing the throughput of data-driven based streaming in heterogeneous overlay network

Authors:
Meng Zhang;Chunxiao Chen;Yongqiang Xiong;Qian Zhang;Shiqiang Yang
Affiliations:
Dept. of Computer Sci. & Tech., Tsinghua Univ., Beijing, China;Dept. of Computer Sci. & Tech., Tsinghua Univ., Beijing, China;Microsoft Research Asia, Beijing, China;Dept. of Computer Sci., Hong Kong Univ. of Sci. and Tech., Hong Kong, China;Dept. of Computer Sci. & Tech., Tsinghua Univ., Beijing, China
Venue:
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Year:
2007

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Abstract

Recently, much attention has been paid on data-driven (or swarm-like) based live streaming systems due to its rapid growth in deployment over Internet. In such systems, nodes randomly select their neighbors to form an unstructured overlay mesh (gossip-style overlay construction) and then each node requests desired data blocks from its neighbors (block scheduling). To improve the performance, most of existing works focus on the gossip-style overlay construction issue; however few concentrate on optimizing the block scheduling for improving the throughput of a constructed overlay, especially in heterogeneous environment. In this paper, we propose a scheme to optimize the throughput of data-driven streaming systems in heterogeneous overlay network. We first model the block scheduling problem as a classical min-cost flow problem and thereby derive a global optimal solution. Based on this idea, we then propose DONLE – a fully distributed asynchronous scheduling algorithm. Simulation results verify that DONLE is superior to a number of conventional strategies.