Minimum-Cost Load-Balancing Partitions

Boris Aronov, Paz Carmi, Matthew J. Katz

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We consider the problem of balancing the load among several service-providing facilities, while keeping the total cost low. Let D be the underlying demand region, and let p 1,p m be m points representing m facilities. We consider the following problem: Subdivide D into m equal-area regions R 1,R m , so that region R i is served by facility p i , and the average distance between a point q in D and the facility that serves q is minimal. We present constant-factor approximation algorithms for this problem, with the additional requirement that the resulting regions must be convex. As an intermediate result we show how to partition a convex polygon into m equal-area convex subregions so that the fatness of the resulting regions is within a constant factor of the fatness of the original polygon. In fact, we prove that our partition is, up to a constant factor, the best one can get if one's goal is to maximize the fatness of the least fat subregion. We also discuss the structure of the optimal partition for the aforementioned load balancing problem: indeed, we argue that it is always induced by an additive-weighted Voronoi diagram for an appropriate choice of weights.

Original languageEnglish
Pages (from-to)318-336
Number of pages19
JournalAlgorithmica
Volume54
Issue number3
DOIs
StatePublished - 1 Jul 2009

Keywords

  • Additive-weighted Voronoi diagram
  • Approximation algorithms
  • Fat partitions
  • Fatness
  • Geometric optimization
  • Load balancing

ASJC Scopus subject areas

  • General Computer Science
  • Computer Science Applications
  • Applied Mathematics

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