Markov regenerative stochastic petri nets to model and evaluate the dependability of phased missions

This study deals with model based dependability analysis of phased mission systems. From a comprehensive review of the studies in the literature, it appears that several aspects of multi phased systems still pose insurmountable problems for the dependability evaluation methods and tools. To address the weak points of the state-of--the--art we propose a modeling methodology that exploits the power of the class of Markov regenerative stochastic Petri net models. Our approach considerably enlarges the class of phased mission systems that can be analytically studied. It can accommodate in a compact and neat modeling all thosepeculiar aspects of phased mission systems that could not be dealt with up to now. By taking advantage of the special structure of phased mission systems, we develop an analytical solution technique with a low computational complexity, basically dominated by the cost of the separate analysis of the system inside each phase. Last, the existence of analytical solutions allows us to derive the sensitivity functions of the dependability measures, thus providing the dependability engineer with additional means for the study of phased mission systems.