Stochastic automata network of modeling parallel systems

A methodology for modeling a system composed of parallel activities with synchronization points is proposed. Specifically, an approach based on a modular state-transition representation of a parallel system called the stochastic automata network (SAN) is developed. The state-space explosion is handled by a decomposition technique. The dynamic behavior of the algorithm is analyzed under Markovian assumptions. The transition matrix of the chain is automatically derived using tensor algebra operators, under a format which involves a very limited storage cost