A self-stabilizing algorithm for maximal matching
Information Processing Letters
Maximal matching stabilizes in quadratic time
Information Processing Letters
Self-stabilization
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Maximal matching stabilizes in time O(m)
Information Processing Letters
Dynamic and self-stabilizing distributed matching
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Self-Stabilizing Protocols for Maximal Matching and Maximal Independent Sets for Ad Hoc Networks
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Efficient Self-stabilizing Algorithms for Tree Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Self-stabilizing Cuts in Synchronous Networks
SIROCCO '08 Proceedings of the 15th international colloquium on Structural Information and Communication Complexity
A Self-stabilizing $\frac{2}{3}$-Approximation Algorithm for the Maximum Matching Problem
SSS '08 Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Journal of Parallel and Distributed Computing
A self-stabilizing algorithm for cut problems in synchronous networks
Theoretical Computer Science
A self-stabilizing weighted matching algorithm
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
Algorithms and theory of computation handbook
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
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The maximal matching problem has received considerable attention in the self-stabilizing community. Previous work has given different self-stabilizing algorithms that solves the problem for both the adversarial and fair distributed daemon, the sequential adversarial daemon, as well as the synchronous daemon. In the following we present a single self-stabilizing algorithm for this problem that unites all of these algorithms in that it stabilizes in the same number of moves as the previous best algorithms for the sequential adversarial, the distributed fair, and the synchronous daemon. In addition, the algorithm improves the previous best moves complexities for the distributed adversarial daemon from O(n2) and O(δm) to O(m) where n is the number of processes, m is the number of edges, and δ is the maximum degree in the graph.