A fast and simple randomized parallel algorithm for maximal matching
Information Processing Letters
Parallel symmetry-breaking in sparse graphs
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Fast distributed construction of small k-dominating sets and applications
Journal of Algorithms
Data structures for weighted matching and nearest common ancestors with linking
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Parallel approximation algorithms for maximum weighted matching in general graphs
Information Processing Letters
Dynamic and self-stabilizing distributed matching
Proceedings of the twenty-first annual symposium on Principles of distributed computing
An O(v|v| c |E|) algoithm for finding maximum matching in general graphs
SFCS '80 Proceedings of the 21st Annual Symposium on Foundations of Computer Science
Linear time 1/2 -approximation algorithm for maximum weighted matching in general graphs
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Distributed approximate matching
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Improved distributed approximate matching
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
A simple local 3-approximation algorithm for vertex cover
Information Processing Letters
Information Processing Letters
ACM Computing Surveys (CSUR)
Lower bounds for local approximation
Journal of the ACM (JACM)
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In this paper, we study distributed algorithms to compute a weighted matching that have constant (or at least sub-logarithmic) running time and that achieve approximation ratio 2 + ε or better. In fact we present two such synchronous algorithms, that work on arbitrary weighted trees The first algorithm is a randomised distributed algorithm that computes a weighted matching of an arbitrary weighted tree, that approximates the maximum weighted matching by a factor 2 + ε. The running time is O(1). The second algorithm is deterministic, and approximates the maximum weighted matching by a factor 2 + ε, but has running time O(log* |V|). Our algorithms can also be used to compute maximum unweighted matchings on regular and almost regular graphs within a constant approximation