A Composition Approach to Performance Modelling
Abstract
Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more easily modelled. In this thesis a novel compositional approach to performance modelling is presented. This approach is based on a suitably enhanced process algebra, PEPA (Performance Evaluation Process Algebra). The compositional nature of the language provides benefits for model solution as well as model construction. An operational semantics is provided for PEPA and its use to generate an underlying Markov process for any PEPA model is explained and demonstrated. Model simplification and state space aggregation have been proposed as means to tackle the problems of large performance models. These techniques are presented in terms of notions of equivalence between modelling entities. A framewo