Expected Impulsive Rewards in Markov Regenerative Stochastic Petri Nets

Reward structures provide a versatile tool for the de nition of performance and dependability measures in stochastic Petri nets In this paper we derive formulas for the computation of expected reward measures in Markov regenerative stochastic Petri nets which allow for transitions with non exponentially distributed ring times The reward measures may be composed of rate rewards which are obtained in certain markings and of impulse rewards which are obtained when transitions re The main result of the paper is the derivation of formulas for the ex pected impulse reward of transitions with non exponentially distributed ring times The analysis is based on the method of supplementary vari ables Numerical examples are given for an M D K queueing system with service breakdowns