Markov and Markov reward model transient analysis: An overview of numerical approaches

The advent of fault-tolerant, distributed systems has led to increased interest in analytic techniques for the prediction of reliability, availability, and combined performance and reliability measures. Markov and Markov reward models are common tools for fault-tolerant system reliability prediction. In this paper, the authors first derive instantaneous and cumulative measures of Markov and Markov reward model behavior. They then compare the complexity of several competing algorithms for the computation of these measures. Better approaches for Markov model solution should lead to more effective tehniques for fault-tolerant system modeling.