A Stochastic Modeling Approach for an Efficient Dependability Evaluation of Large Systems with Non-anonymous Interconnected Components

This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, interconnected with each other according to a variety of topologies. A new efficient replication technique is presented and its implementation is discussed. The goal is to improve the performance of simulation solvers with respect to standard approaches, when employed in the modeling of the addressed class of systems, in particular for loosely interconnected system components (as typically encountered in the electrical or transportation sectors). Effectiveness of the new technique is demonstrated by comparison with a state of the art alternative solution on a representative case study.