We use a structural operational semantics which drives us in inferring quantitative measures on system evolution. The transitions of the system are labelled and we assign rates to them by only looking at these labels. The rates reflect the possibly distributed architecture on which applications run. We then map transition systems to Markov chains, and performance evaluation is carried out using standard tools. As a working example, we compare the performance of a conventional uniprocessor with a prefetch pipeline machine. We also consider two case studies from the literature involving mobile computation to show that our framework is feasible.

Abstract. We propose a structural operational semantics for mobile and distributed agents. From it we derive a stochastic transition system labelled by actions and their costs. These costs reflect the (net) architecture on which agents run. We then map stochastic transition systems to Markov chains, and performance evaluation is carried out using standard tools. The results of our approach are shown to agree with the ones obtained via classical evaluation techniques on a case study involving mobile computation.