Year: 2010
Type: preprint
Abstract: The syntactic nature and compositionality characteristic of stochastic process algebras make models to be easily understood by human beings, but not convenient for machines as well as people to directly carry out mathematical analysis and stochastic simulation. This paper presents a numerical representation schema for the stochastic process algebra PEPA, which can provide a platform to directly and conveniently employ a variety of computational approaches to both qualitatively and quantitatively analyse the models. Moreover, these approaches developed on the basis of the schema are demonstrated and discussed. In particular, algorithms for automatically deriving the schema from a general PEPA model and simulating the model based on the derived schema to derive performance measures are presented.
Source: arXiv (Cornell University)
Authors: Ding, Jie, Hillston, Jane
Institutions: Yangzhou University, University of Edinburgh
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3076088