A self-stabilizing algorithm for constructing spanning trees
Information Processing Letters
A self-stabilizing algorithm for maximal matching
Information Processing Letters
Fault-containing self-stabilizing algorithms
PODC '96 Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing
Time-adaptive self stabilization
PODC '97 Proceedings of the sixteenth annual ACM symposium on Principles of distributed computing
Asynchronous time-adaptive self stabilization
PODC '98 Proceedings of the seventeenth annual ACM symposium on Principles of distributed computing
Optimal reactive k-stabilization: the case of mutual exclusion
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
DISC '98 Proceedings of the 12th International Symposium on Distributed Computing
ICDCS '99 Workshop on Self-stabilizing Systems
ISTCS '97 Proceedings of the Fifth Israel Symposium on the Theory of Computing Systems (ISTCS '97)
Superstabilizing Protocols for Dynamic Distributed Systems
Superstabilizing Protocols for Dynamic Distributed Systems
Self-stabilizing algorithm for checkpointing in a distributed system
Journal of Parallel and Distributed Computing
A framework of safe stabilization
SSS'03 Proceedings of the 6th international conference on Self-stabilizing systems
Algorithms and theory of computation handbook
Self-stabilizing checkpointing algorithm in ring topology
IWDC'05 Proceedings of the 7th international conference on Distributed Computing
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This paper presents a methodology for a synchronous non-reactive distributed system on a tree topology to stabilize from a k-faulty configuration in a time independent of the size n of the system. In the proposed methodology, processes first measure and compare the sizes of the faulty regions, and then use this information to schedule actions in such a way that the size of the faulty regions progressively shrink, until they completely disappear. We demonstrate that when k processes fail, the stabilization time is O(k2). Apart from its applicability to a wide class of problems, the proposed method achieves scalability with a low space complexity of O(Δ.(Δ.k + log2 n)) per process, where Δ is the maximum degree of a node.