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An Aggregation Technique for Large-Scale PEPA Models with Non-Uniform Populations

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Original languageEnglish
Title of host publicationProceedings of ValueTools 2013 - 7th International Conference on Performance Evaluation Methodologies and Tools
PublisherICST
Number of pages10
Edition7
DOIs
Publication statusPublished - 9 Dec 2013
EventValueTools 2013 -- 7th International Conference on Performance Evaluation Methodologies and Tools - Lingotto, Torino, Andorra
Duration: 10 Dec 201312 Dec 2013

Conference

ConferenceValueTools 2013 -- 7th International Conference on Performance Evaluation Methodologies and Tools
CountryAndorra
CityTorino
Period10/12/1312/12/13

Abstract

Performance analysis based on modelling consists of two major steps: model construction and model analysis. Formal modelling techniques significantly aid model construction but can exacerbate model analysis. In particular, here we consider the analysis of large-scale systems which consist of one or more entities replicated many times to form large populations. The replication of entities in such models can cause their state spaces to grow exponentially to the extent that their exact stochastic analysis becomes computationally expensive or even infeasible.
In this paper, we propose a new approximate aggregation
algorithm for a class of large-scale PEPA models. For a
given model, the method quickly checks if it satises a syn-
tactic condition, indicating that the model may be solved
approximately with high accuracy. If so, an aggregated
CTMC is generated directly from the model description.
This CTMC can be used for ecient derivation of an ap-
proximate marginal probability distribution over some of
the model's populations. In the context of a large-scale
client-server system, we demonstrate the usefulness of our
method.

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