Markov Regenerative Stochastic Petri Nets to Model and Evaluate Phased Mission Systems Dependability
IEEE Transactions on Computers
Dependability Modelling and Sensitivity Analysis of Scheduled Maintenance Systems
EDCC-3 Proceedings of the Third European Dependable Computing Conference on Dependable Computing
Resilience in computer systems and networks
Proceedings of the 2009 International Conference on Computer-Aided Design
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Most reliability analysis techniques and tools assume that a system is used for a mission consisting of a single phase. However, multiple phases are natural in many missions. The failure rates of components, system configuration, and success criteria may vary from phase to phase. In addition, the duration of a phase may be deterministic or random. Recently, several researchers have addressed the problem of reliability analysis of such systems using a variety of methods. We describe a new technique for phased-mission system reliability analysis based on Boolean algebraic methods. Our technique is computationally efficient and is applicable to a large class of systems for which the failure criterion in each phase can be expressed as a fault tree (or an equivalent representation). Our technique avoids state space explosion that commonly plague Markov chain-based analysis. We develop a phase algebra to account for the effects of variable configurations and success criteria from phase to phase. Our technique yields exact (as opposed to approximate) results. We demonstrate the use of our technique by means of an example and present numerical results to show the effects of mission phases on the system reliability.