Large-scale Performance Models with Stochastic Process Algebras

This talk gives an overview of recent research concerning the use of stochastic process algebras for the quantitative evaluation of computer systems. The talk consists of three parts. The first part will introduce some basic notions on the usual discrete-state semantics in terms of continuous-time Markov chains. The second part will focus on the stochastic process algebra PEPA and discuss its fluid interpretation, a deterministic approximation with ordinary differential equations for the analysis of large-scale models. Finally, the third part will discuss how to compute typical measures of performance such as utilisation, throughput, and average response times from fluid models. Backed by theoretical results of asymptotic convergence, extensive numerical assays will show good accuracy of this approach for all practical purposes.