Online Bottleneck Matching

  • Barbara M. Anthony
  • Christine Chung
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7402)


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. 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.


Competitive Ratio Online Algorithm Match Problem Response Graph Primary Server 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Barbara M. Anthony
    • 1
  • Christine Chung
    • 2
  1. 1.Math and Computer Science DepartmentSouthwestern UniversityGeorgetownUSA
  2. 2.Department of Computer ScienceConnecticut CollegeNew LondonUSA

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