Finding graph matchings in data streams

Authors:
Andrew McGregor
Affiliations:
Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA
Venue:
APPROX'05/RANDOM'05 Proceedings of the 8th international workshop on Approximation, Randomization and Combinatorial Optimization Problems, and Proceedings of the 9th international conference on Randamization and Computation: algorithms and techniques
Year:
2005

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Abstract

We present algorithms for finding large graph matchings in the streaming model. In this model, applicable when dealing with massive graphs, edges are streamed-in in some arbitrary order rather than residing in randomly accessible memory. For ε0, we achieve a $\frac1{1+\epsilon}$ approximation for maximum cardinality matching and a $\frac1{2+\epsilon}$ approximation to maximum weighted matching. Both algorithms use a constant number of passes and $\tilde O(|V|)$ space.