Trivedi, K.S., J.M. Muppala, S.P. Woolet and B.R. Haverkort, Composite performance and dependability analysis, Performance Evaluation 14 (1992) 197-215. Composite performance and dependability analysis is gaining importance in the design of complex, fault-tolerant systems. Markov reward models are most commonly used for this purpose. In this paper, an introduction to Markov reward models includ...

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 [l], [2]. Markov or semi-Markov reward models can be used to evaluate th...

We analyze derivation of Markov reward chains from intermediate performance models that arise from formalisms for compositional performance analysis like stochastic process algebras, (generalized) stochastic Petri nets, etc. The intermediate models are typically extensions of continuous-time Markov reward chains with instantaneous labeled transitions. We give stochastic meaning to the intermedi...

The analysis of Markov Reward Models with preemptive resume policy usually results in a double transform expression, whose solution is based on an inverse transformation, both in the time and in the reward variable domains. This paper discusses the case when the reward rates can be described only by 0 or positive c values. These on-o Markov Reward Models are analyzed and a symbolic solution is ...

Analysis of Markov reward models with stochastic Petri nets is presented. Generation methods and analysis of continuous-time Markov chains and Markov reward models is provided for modeling of reliability of very large systems and working out measures for their performance. Examples and numerical results for M/D/1/2/2 system are shown.

Numerous applications in the area of computer system analysis can be effectively studied with Markov reward models. These models describe the behavior of the system with a continuous-time Markov chain, where a reward rate is associated with each state. In a reliability/availability model, upstates may have reward rate 1 and down states may have reward rate zero associated with them. In a queuei...