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 ε> 0, 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.
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McGregor, A. (2005). Finding Graph Matchings in Data Streams. In: Chekuri, C., Jansen, K., Rolim, J.D.P., Trevisan, L. (eds) Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques. APPROX RANDOM 2005 2005. Lecture Notes in Computer Science, vol 3624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538462_15
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DOI: https://doi.org/10.1007/11538462_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28239-6
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