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Approximation algorithms for data placement in arbitrary networks

Published: 09 January 2001 Publication History

Abstract

We study approximation algorithms for placing replicated data in arbitrary networks. Consider a network of nodes with individual storage capacities and a metric communication cost function, in which each node periodically issues a request for an object drawn from a collection of uniform-length objects. We consider the problem of placing copies of the objects among the nodes such that the average access cost is minimized. Our main result is a polynomial-time constant-factor approximation algorithm for this placement problem. Our algorithm is based on a careful rounding of a linear programming relaxation of the problem. We also show that the data placement problem is MAXSNP-hard.
We extend our approximation result to a generalization of the data placement problem that models additional costs such as the cost of realizing the placement. We also show that when object lengths are non-uniform, a constant-factor approximation is achievable if the capacity at each node in the approximate solution is allowed to exceed that in the optimal solution by the length of the largest object.

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cover image ACM Conferences
SODA '01: Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
January 2001
937 pages
ISBN:0898714907

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Society for Industrial and Applied Mathematics

United States

Publication History

Published: 09 January 2001

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Overall Acceptance Rate 411 of 1,322 submissions, 31%

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