Abstract
We introduce a framework to study stochastic systems, i.e. systems in which the time of occurrence of activities is a general random variable. We introduce and discuss in depth a stochastic process algebra (named ♤) adequate to specify and analyse those systems. In order to give semantics to ♤, we also introduce a model that is an extension of traditional automata with clocks which are basically random variables: the stochastic automata model. We show that this model and ♤ are equally expressive. Although stochastic automata are adequate to analyse systems since they are finite objects, they are still too coarse to serve as concrete semantic objects. Therefore, we introduce a type of probabilistic transition system that can deal with arbitrary probability spaces. In addition, we give a finite axiomatisation for ♤ that is sound for the several semantic notions we deal with, and complete for the finest of them. Moreover, an expansion law is straightforwardly derived.
Original language | English |
---|---|
Title of host publication | Programming Concepts and Methods PROCOMET ’98 |
Subtitle of host publication | IFIP TC2 / WG2.2, 2.3 International Conference on Programming Concepts and Methods (PROCOMET ’98) 8–12 June 1998, Shelter Island, New York, USA |
Editors | David Gries, Willem-Paul de Roever |
Publisher | Chapman & Hall |
Chapter | 12 |
Pages | 126-147 |
Number of pages | 22 |
ISBN (Electronic) | 978-0-387-35358-6 |
ISBN (Print) | 0-412-83750-9 |
DOIs | |
Publication status | Published - Jun 1998 |
Event | IFIP TC2/WG2.2,2.3 International Conference on Programming Concepts and Methods, PROCOMET 1998 - Shelter Island, United States Duration: 8 Jun 1998 → 12 Jun 1998 |
Conference
Conference | IFIP TC2/WG2.2,2.3 International Conference on Programming Concepts and Methods, PROCOMET 1998 |
---|---|
Abbreviated title | PROCOMET |
Country/Territory | United States |
City | Shelter Island |
Period | 8/06/98 → 12/06/98 |
Keywords
- FMT-PA: PROCESS ALGEBRAS
- FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS
- Stochastic process algebras
- Stochastic automata
- Probabilistic transition systems
- Probabilistic bisimulations
- Real-time systems