PERFORMANCE ANALYSIS OF MARKOV REGENERATIVE REWARD MODELS

The problem considered in the paper can not be solved by the tradition al technique available for the analysis of Markov Regenerative Process es (MRGP). The widely used description of MRGPs, i.e. by the local and the global kernels, do not contain sufficient information on the proc ess to evaluate the distribution of reward measures. A new analytical approach is proposed and studied to utilize better the Markov regenera tive property for the analysis of Markov Regenerative Reward Models (M RRM). The distribution of the accumulated reward and the completion ti me of MRRMs is provided in transform domain, as well as considerations about the time domain numerical evaluation of these measures. As a si mple application example the performance of a finite queueing system i s analyzed.