DocumentCode :
2022952
Title :
Process algebras for quantitative analysis
Author :
Hillston, J.
Author_Institution :
LFCS, Edinburgh Univ., UK
fYear :
2005
fDate :
26-29 June 2005
Firstpage :
239
Lastpage :
248
Abstract :
In the 1980s process algebras became widely accepted formalisms for describing and analysing concurrency. Extensions of the formalisms, incorporating some aspects of systems which had previously been abstracted, were developed for a number of different purposes. In the area of performance analysis models must quantify both timing and probability. Addressing this domain led to the formulation of stochastic process algebras. In this paper we give a brief overview of stochastic process algebras and the problems which motivated them, before focussing on their relationship with the underlying mathematical stochastic process. This is presented in the context of the PEPA formalism.
Keywords :
probability; process algebra; stochastic processes; PEPA formalism; mathematical stochastic process; performance analysis model; probability; process algebras; quantitative analysis; Algebra; Concurrent computing; Context; Informatics; Markov processes; Performance analysis; Power system modeling; Sparse matrices; Stochastic processes; Timing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Logic in Computer Science, 2005. LICS 2005. Proceedings. 20th Annual IEEE Symposium on
ISSN :
1043-6871
Print_ISBN :
0-7695-2266-1
Type :
conf
DOI :
10.1109/LICS.2005.35
Filename :
1509228
Link To Document :
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