article

Competitive randomized algorithms for nonuniform problems

Authors:

S. OwickiAuthors Info & Claims

Algorithmica, Volume 11, Issue 6

Pages 542 - 571

https://doi.org/10.1007/BF01189993

Published: 01 June 1994 Publication History

Abstract

Competitive analysis is concerned with comparing the performance of on-line algorithms with that of optimal off-line algorithms. In some cases randomization can lead to algorithms with improved performance ratios on worst-case sequences. In this paper we present new randomized on-line algorithms for snoopy caching and the spin-block problem. These algorithms achieve competitive ratios approachinge/(eź1) ź 1.58 against an oblivious adversary. These ratios are optimal and are a surprising improvement over the best possible ratio in the deterministic case, which is 2. We also consider the situation when the request sequences for these problems are generated according to an unknown probability distribution. In this case we show that deterministic algorithms that adapt to the observed request statistics also have competitive factors approachinge/(eź1). Finally, we obtain randomized algorithms for the 2-server problem on a class of isosceles triangles. These algorithms are optimal against an oblivious adversary and have competitive ratios that approache/(eź1). This compares with the ratio of 3/2 that can be achieved on an equilateral triangle.

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cover image Algorithmica

Algorithmica Volume 11, Issue 6

June 1994

78 pages

ISSN:0178-4617

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Copyright © Copyright © 1994 Springer-Verlag New York Inc.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 1994

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