Efficient Algorithms for Optimal Stream Merging for Media-on-Demand

نویسندگان

Amotz Bar-Noy

Richard E. Ladner

چکیده

We address the problem of designing optimal off-line algorithms that minimize the required bandwidth for media-on-demand systems that use stream merging. We concentrate on the case where clients can receive two media streams simultaneously and can buffer up to half of a full stream. We construct an O(nm) optimal algorithm for n arbitrary time arrivals of clients, where m is the average number of arrivals in an interval of a stream length. We then show how to adopt our algorithm to be optimal even if clients have a limited size buffer. The complexity remains the same. We also prove that using stream merging may reduce the required bandwidth by a factor of order ρL/ log(ρL) compared to the simple batching solution where L is the length of a stream and ρ ≤ 1 is the density in time of all the n arrivals. On the other hand, we show that the bandwidth required when clients can receive an unbounded number of streams simultaneously is always at least 1/2 the bandwidth required when clients are limited to receiving at most two streams. Address: Computer and Information Science Department, Brooklyn College – CUNY, 2900 Bedford Avenue, Brooklyn, NY 11210. E-mail: [email protected]. This work was done in part while the author was a member of the AT&T Labs-Research, Shannon Lab, Florham Park, NJ. Address: Department of Computer Science and Engineering, Box 352350, University of Washington, Seattle, WA 98195. E-mail: [email protected]. 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.

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Efficient algorithms for optimal stream merging for media-on-demand

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