Journal of Combinatorial Optimization

, Volume 27, Issue 1, pp 100–114

Online bottleneck matching

Authors

    • Mathematics and Computer Science DepartmentSouthwestern University
  • Christine Chung
    • Department of Computer ScienceConnecticut College
Article

DOI: 10.1007/s10878-012-9581-9

Cite this article as:
Anthony, B.M. & Chung, C. J Comb Optim (2014) 27: 100. doi:10.1007/s10878-012-9581-9

Abstract

We consider the online bottleneck matching problem, where \(k\) server-vertices lie in a metric space and \(k\) request-vertices that arrive over time each must immediately be permanently assigned to a server-vertex. The goal is to minimize the maximum distance between any request and its server. Because no algorithm can have a competitive ratio better than \(O(k)\) for this problem, we use resource augmentation analysis to examine the performance of three algorithms: the naive Greedy algorithm, Permutation, and Balance. We show that while the competitive ratio of Greedy improves from exponential (when each server-vertex has one server) to linear (when each server-vertex has two servers), the competitive ratio of Permutation remains linear when an extra server is introduced at each server-vertex. The competitive ratio of Balance is also linear with an extra server at each server-vertex, even though it has been shown that an extra server makes it constant-competitive for the min-weight matching problem.

Keywords

Online algorithms Bottleneck matching Resource augmentation Approximation algorithms Matching

Copyright information

© Springer Science+Business Media New York 2012