Journal of Combinatorial Optimization

, Volume 27, Issue 1, pp 100–114 | Cite as

Online bottleneck matching

  • Barbara M. Anthony
  • Christine Chung


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.


Online algorithms Bottleneck matching Resource augmentation Approximation algorithms Matching 


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Mathematics and Computer Science DepartmentSouthwestern UniversityGeorgetownUSA
  2. 2.Department of Computer ScienceConnecticut CollegeNew LondonUSA

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