PERFORMABILITY ANALYSIS USING SEMI-MARKOV REWARD PROCESSES

With the increasing complexity of multiprocessor and distributed processing systems, the need to develop efficient and accurate modeling methods is evident. Fault tolerance and degradable performance of such systems has given rise to considerable interest in models for the combined evaluation of performance and reliability [1], [2]. Markov or semi-Markov reward models can be used to evaluate the effectiveness of degradable fault-tolerant systems. Beaudry [1] proposed a simple method for computing the distribution of performability in a Markov reward process. We present two extensions of Beaudry’s approach. First, we generalize the method to a semi-Markov reward process. Second, we remove the restriction requiring the association of zero reward to absorbing states only. We illustrate the use of the approach with three interesting applications. © 1990 IEEE