Self-stabilization by local checking and correction (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Locality in distributed graph algorithms
SIAM Journal on Computing
An exercise in fault-containment: self-stabilizing leader election
Information Processing Letters
Fault-containing network protocols
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Self-stabilization
Fault-containing self-stabilization using priority scheduling
Information Processing Letters
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Self-Stabilization by Local Checking and Global Reset (Extended Abstract)
WDAG '94 Proceedings of the 8th International Workshop on Distributed Algorithms
An Efficient Fault-Containing Self-Stabilizing Algorithm for Finding a Maximal Independent Set
IEEE Transactions on Parallel and Distributed Systems
Linear time self-stabilizing colorings
Information Processing Letters
Algorithms and theory of computation handbook
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Self-stabilization guarantees convergence to a legitimate configuration in every execution starting from any initial configuration. However, during convergence, most self-stabilizing protocols make unnecessary output changes that do not directly contribute to the progress of convergence. We define and study monotonic stabilization, where every output change is a step toward convergence. That is, any output change at a process p gives the final output of p in the legitimate configuration to be reached. It turns out that monotonic stabilization requires additional information exchange between processes, and we present task dependent tradeoff results with respect to the locality of exchanged information.