Volume 6: Materials and Fabrication, Parts a and B 2011
DOI: 10.1115/pvp2011-57683
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Identifying Failure Scenarios in Complex Systems by Perturbing Markov Chain Models

Abstract: In recent years, substantial research has been devoted to monitoring and predicting performance degradations in real-world complex systems within large entities such as nuclear power plants, electrical grids, and distributed computing systems. Special challenges are posed by the fact that such systems operate in uncertain environments, are highly dynamic, and exhibit emergent behaviors that can lead to catastrophic failure. Discrete Time Markov chains (DTMCs) provide important tools for analysis of such system… Show more

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Cited by 2 publications
(2 citation statements)
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“…In paper [35] used a Discrete Time Markov Chain as a fault detection mechanism in their proposed solution. They also incorporate a long-term condition monitoring of equipment in the complex systems.…”
Section: B Resource Monitoringmentioning
confidence: 99%
See 1 more Smart Citation
“…In paper [35] used a Discrete Time Markov Chain as a fault detection mechanism in their proposed solution. They also incorporate a long-term condition monitoring of equipment in the complex systems.…”
Section: B Resource Monitoringmentioning
confidence: 99%
“…Although the HA features do make a positive outcome, especially when the situation of resource contention arise but, the SLA with the client is cramping the provider. A fault tolerance mechanism should be incorporated with the monitoring suite for the resources.In paper [35] used a Discrete Time Markov Chain as a fault detection mechanism in their proposed solution. They also incorporate a long-term condition monitoring of equipment in the complex systems.…”
mentioning
confidence: 99%