Online Bottleneck Matching

This is an Accepted Manuscript of an article published by Springer in Journal of Combinatorial Optimization, 2012, 27(1), 100–114. http://doi.org/10.1007/s10878-012-9581-9

Anthony, Barbara M.

Chung, Christine

2016-06-15

2016-06-15

2012

Anthony, B. M., & Chung, C. (2012). Online bottleneck matching. Journal of Combinatorial Optimization, 27(1), 100–114. http://doi.org/10.1007/s10878-012-9581-9

https://collections.southwestern.edu/s/suscholar/item/217

We consider the online bottleneck matching problem, where kk server-vertices lie in a metric space and kk 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)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.

English

Springer http://link.springer.com/article/10.1007/s10878-012-9581-9

Online algorithms

Bottleneck matching

Resource augmentation

Approximation algorithms

Matching

Research Subject Categories::MATHEMATICS

Article