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- W2801164407 abstract "The analysis of self-stabilizing algorithms is often limited to the worst case stabilization time starting from an arbitrary state, i.e., a state resulting from a sequence of faults. Considering the fact that these algorithms are intended to provide fault tolerance in the long run, this is not the most relevant metric. A common situation is that a running system is an a legitimate state when hit by a single fault. This event has a much higher probability than multiple concurrent faults. Therefore, the worst case time to recover from a single fault is more relevant than the recovery time from a large number of faults. This paper presents techniques to derive upper bounds for the mean time to recover from a single fault for self-stabilizing algorithms based on Markov chains in combination with lumping. To illustrate the applicability of the techniques they are applied to a new self-stabilizing coloring algorithm." @default.
- W2801164407 created "2018-05-17" @default.
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- W2801164407 date "2018-05-03" @default.
- W2801164407 modified "2023-09-26" @default.
- W2801164407 title "Computing Fault-Containment Times of Self-Stabilizing Algorithms Using Lumped Markov Chains" @default.
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- W2801164407 doi "https://doi.org/10.3390/a11050058" @default.
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