Abstract. We develop an algorithm to compute timed reachability probabilities for distributed models which are both probabilistic and nondeterministic. To obtain realistic results we consider the recently introduced class of (strongly) distributed schedulers, for which no analysis techniques are known. Our algorithm is based on reformulating the nondeterministic models as parametric ones, by interpreting scheduler decisions as parameters. We then apply the PARAM tool to extract the reachability probability as a polynomial function, which we optimize using nonlinear programming. Key words: Distributed Systems, Probabilistic Models, Nondeterminism, Time-Bounded Reachability
Georgel Calin, Pepijn Crouzen, Pedro R. D'Argenio,