2013 IEEE 32nd International Symposium on Reliable Distributed Systems 2013
DOI: 10.1109/srds.2013.24
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Rigorous Performance Evaluation of Self-Stabilization Using Probabilistic Model Checking

Abstract: We propose a new metric for effectively and accurately evaluating the performance of self-stabilizing algorithms. Self-stabilization is a versatile category of fault-tolerance that guarantees system recovery to normal behavior within a finite number of steps, when the state of the system is perturbed by transient faults (or equally, the initial state of the system can be some arbitrary state). The performance of self-stabilizing algorithms is conventionally characterized in the literature by asymptotic computa… Show more

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Cited by 15 publications
(5 citation statements)
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“…Bounding latencies is of utmost importance, but this is quite difficult in the presence of changes [5,6,14,24,25,42]. Changes are unpredictable, they can be dramatic, and they can include malfunctioning [23], slow down [12], failures [18], and much more. Graceful degradation [31] is then introduced into the runtime system, to handle these changes and guarantee performance in the presence of uncertainty.…”
Section: B Experimental Resultsmentioning
confidence: 99%
“…Bounding latencies is of utmost importance, but this is quite difficult in the presence of changes [5,6,14,24,25,42]. Changes are unpredictable, they can be dramatic, and they can include malfunctioning [23], slow down [12], failures [18], and much more. Graceful degradation [31] is then introduced into the runtime system, to handle these changes and guarantee performance in the presence of uncertainty.…”
Section: B Experimental Resultsmentioning
confidence: 99%
“…A more challenging avenue of research is to not only parameterize the probability function, but also make the computational model parametric in terms of the number of processes. Finally, we can use our techniques to automatically generate state encoding [14,15] schemes to orthogonally improve the recovery time.…”
Section: Discussionmentioning
confidence: 99%
“…This paper addresses the aforementioned problem in the context of randomized self-stabilizing systems. Following the results in [14,15], our choice of performance metric is average recovery time. In particular, we propose a fully automated technique that takes as input a randomized selfstabilizing algorithm, where processes execute their actions with some probability, and generates as output the probability value based on which, the self-stabilizing algorithm exhibits the minimum average recovery time.…”
Section: Our Contribution-synthesizing Optimal Biasmentioning
confidence: 99%
See 1 more Smart Citation
“…In the context of self-stabilization, a new metric has been proposed to measure the recovery performance of an algorithm, the expected number of recovery steps [34]. An equivalent metric, the number of control decisions to recovery, could be used by a service operator for tuning the service to the expected capacity drop and the request servicing time of the replicas.…”
Section: Discussionmentioning
confidence: 99%