Approximate performability analysis using generalized stochastic Petri nets

Addresses the problem of calculating performability measures from performability models of fault-tolerant computer systems. Since these systems tend to be large and complex, the corresponding performability models will in general also be large and complex. To alleviate the largeness problem to some extent the author uses generalized stochastic Petri nets to describe the models. Still however, many models cannot be solved with the current numerical techniques, although they are conveniently and often compactly described. In the paper the author discusses two heuristic state space truncation techniques that allow us to obtain very good approximations while only assessing a few percent of the overall state space. He gives examples of the usage, but also theoretical evidence in the correctness of the employed truncation techniques. He furthermore shows that GSPNs are very suitable for implementing (describing) the proposed truncation techniques