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Return of the primal-dual: distributed metric facilitylocation
Conference proceeding

Return of the primal-dual: distributed metric facilitylocation

Saurav Pandit and Sriram Pemmaraju
Proceedings of the 28th ACM symposium on principles of distributed computing, pp.180-189
PODC '09
08/10/2009
DOI: 10.1145/1582716.1582747

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Abstract

In this paper we present fast, distributed approximation algorithms for the metric facility location problem in the CONGEST model, where message sizes are bounded by O (log N ) bits, N being the network size. We first show how to obtain a 7-approximation in O (log m + log n ) rounds via the primal-dual method; here m is the number of facilities and n is the number of clients. Subsequently, we generalize this to a k -round algorithm, that for every constant k , yields an approximation factor of O ( m 2/√ k ∙ n 3/√ k ). These results answer a question posed by Moscibroda and Wattenhofer ( PODC 2005 ). Our techniques are based on the primal-dual algorithm due to Jain and Vazirani ( JACM 2001 ) and a rapid randomized sparsification of graphs due to Gfeller and Vicari ( PODC 2007 ). These results complement the results of Moscibroda and Wattenhofer ( PODC 2005 ) for non-metric facility location and extend the results of Gehweiler et al. ( SPAA 2006 ) for uniform metric facility location.
approximation algorithms bounded message size facility location unit ball graphs wireless ad-hoc networks

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