Abstract
This paper presents a new algorithm for finding better approximation solutions to the min-cost point coverage problem in wireless sensor networks. The problem is to compute a deterministic sensor deployment plan, with minimum monetary cost on sensors, to cover the set of targets spread across a geographical region such that each target is covered by multiple sensors. This is a Max-SNP-complete problem. Our approximation algorithm, called alpha-beta approximation, is a convex combination of greedy LP-rounding and greedy set-cover selection. We show that, through a large number of numerical simulations on randomly generated targets and sites, alpha-beta approximation produces efficiently better approximation results than the best approximation algorithm previously known. In particular, the alpha-beta approximation in our experiments never exceeds an approximation ratio of 1.07, providing up to 14.86% improvement over previous approximation algorithms.
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© 2008 Springer-Verlag Berlin Heidelberg
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Fang, Z., Wang, J. (2008). Convex Combination Approximation for the Min-Cost WSN Point Coverage Problem. In: Li, Y., Huynh, D.T., Das, S.K., Du, DZ. (eds) Wireless Algorithms, Systems, and Applications. WASA 2008. Lecture Notes in Computer Science, vol 5258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88582-5_20
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DOI: https://doi.org/10.1007/978-3-540-88582-5_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88581-8
Online ISBN: 978-3-540-88582-5
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