A self-stabilizing algorithm for maximal matching
Information Processing Letters
Reaching Agreement in the Presence of Faults
Journal of the ACM (JACM)
Self-stabilization
The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Notes on Data Base Operating Systems
Operating Systems, An Advanced Course
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Self-stabilizing space optimal synchronization algorithms on trees
SIROCCO'06 Proceedings of the 13th international conference on Structural Information and Communication Complexity
SSS'05 Proceedings of the 7th international conference on Self-Stabilizing Systems
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A key problem in designing self-stabilising algorithm is to minimise the stabilisation time (also called convergence time), that is, the maximum time necessary to bring a system into a legitimate configuration after an arbitrary initialisation or after a fault; this process is called stabilisation. Except for Masuzawa and Kakugawa (2005); Nakaminami et al. (2006), it was always measured either from the initial configuration or the configuration after the fault. When a fault has only a local effect, this measure overestimates the time to stabilise, since a system may recover much faster after a fault than after an arbitrary initialisation. We measure the stabilisation time only from the initial configuration. We show the efficiency of this measure that includes as parameter the number of faults, for a consensus algorithm on an oriented chain where processes can join or leave at will.