Stochastic Process Algebras: Linking Process Descriptions with Performance.

In this presentation we will give an overview of the research on stochastic process algebras, a branch of process algebra that has developed over the last decade. Like ordinary process algebra, stochastic process algebra (SPA) provides a compositional model for the description and analysis of complex distributed systems, such as network protocol systems. At the same time SPAs are extended with stochastic features to enable the compositional and systematic derivation of performance models from such descriptions. We will discuss the motivation and potential benefits of the use of SPAs, and present the main conceptual issues in their development. In particular, we will present so-called Markovian process algebras that allow for performance analysis in terms of Continuous Time Markov Chains (CTMC), as well as a non-Markovian process algebra enabling the use of more general performance models.