An Experience on Probabilistic Model Checking and Stochastic Simulation to Design Self-Organizing Systems

The interest in self-organization as a feasible metaphor for dealing with the growing complexity of today’s software systems is constantly rising. In particular, by adopting self-organization, systems can adapt to highly dynamic environments by local interactions among system’s components. As a consequence, the global behavior of the system can be regarded as an emergent property since it appears by a process emerging from local interactions among components. The corresponding system dynamics is usually non-linear and complex so that the adoption of simulation and verification techniques in the early design stage becomes essential to carry out an effective design. Accordingly, in this paper we discuss a hybrid approach relying on stochastic simulation and probabilistic model checking. We show also a possible application of the approach on a problem called collective sort, by adopting the PRISM probabilistic model checker as a concrete tool for analyzing emergent properties. A discussion of the corresponding results is provided.