Self-stabilization
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Self-stabilization with r-operators
Distributed Computing
Stabilization of Routing in Directed Networks
WSS '01 Proceedings of the 5th International Workshop on Self-Stabilizing Systems
Self-stabilization with path algebra
Theoretical Computer Science
Tolerance to Unbounded Byzantine Faults
SRDS '02 Proceedings of the 21st IEEE Symposium on Reliable Distributed Systems
Optimal deterministic self-stabilizing vertex coloring in unidirectional anonymous networks
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
An efficient self-stabilizing distance-2 coloring algorithm
Theoretical Computer Science
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A distributed algorithm is self-stabilizing if after faults and attacks hit the system and place it in some arbitrary global state, the system recovers from this catastrophic situation without external intervention in finite time. Unidirectional networks preclude many common techniques in self-stabilization from being used, such as preserving local predicates. The focus of this work is on the classical vertex coloring problem, that is a basic building block for many resource allocation problems arising in wireless sensor networks. In this paper, we investigate the gain in complexity that can be obtained through randomization. We present a probabilistically selfstabilizing algorithm that uses k states per process, where k is a parameter of the algorithm. When k = Δ + 1, the algorithm recovers in expected O(Δn) actions. When k may grow arbitrarily, the algorithm recovers in expected O(n) actions in total. Thus, our algorithm can be made optimal with respect to space or time complexity. Our case study hints that randomization could help filling the complexity gap between bidirectionnal and unidirectionnal networks.