Abstract.
Stream merging is a technique for efficiently delivering popular media-on-demand using multicast and client buffers. Recently, several algorithms for stream merging have been proposed, and in this paper we perform a comprehensive comparison of these algorithms. We present the differences in philosophy and mechanics among the various algorithms and illustrate the tradeoffs between their system complexity and performance. We measure performance in total, maximum, and time-varying server bandwidth usage under different assumptions for the client request patterns. We also consider the effects on clients when the server has limited bandwidth. The result of this study is a deeper understanding of the system complexity and performance tradeoffs for the various algorithms.
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Amotz Bar-Noy: This work was done in part while the author was a member of the AT&T Labs-Research, Shannon Lab, Florham Park, NJ.
Justin Goshi: Corresponding author. This work was done in part at AT&T Labs-Research, Shannon Lab, Florham Park, NJ.
Richard E. Ladner: This work was done in part at AT&T Labs-Research, Shannon Lab, Florham Park, NJ and partially supported by NSF grants No. CCR-9732828 and CCR-0098012.
A preliminary version of this paper appeared in Multimedia Computing and Networking 2002.
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Bar-Noy, A., Goshi, J., Ladner, R.E. et al. Comparison of stream merging algorithms for media-on-demand. Multimedia Systems 9, 411–423 (2004). https://doi.org/10.1007/s00530-003-0114-3
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DOI: https://doi.org/10.1007/s00530-003-0114-3