Dependability Engineering of Silent Self-stabilizing Systems
Self-stabilization is an elegant way of realizing non-masking fault-tolerant systems. Sustained research over last decades has produced multiple self-stabilizing algorithms for many problems in distributed computing. In this paper, we present a framework to evaluate multiple self-stabilizing solutions under a fault model that allows intermittent transient faults. To that end, metrics to quantify the dependability of self-stabilizing systems are defined. It is also shown how to derive models that are suitable for probabilistic model checking in order to determine those dependability metrics. A heuristics-based method is presented to analyze counterexamples returned by a probabilistic model checker in case the system under investigation does not exhibit the desired degree of dependability. Based on the analysis, the self-stabilizing algorithm is subsequently refined.
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