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dc.contributor.advisorHillston, Jane
dc.contributor.advisorGilmore, Stephen
dc.contributor.authorTribastone, Mirco
dc.date.accessioned2011-01-18T14:10:03Z
dc.date.available2011-01-18T14:10:03Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/1842/4629
dc.description.abstractThe performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the performance evaluation. This is suitable for models consisting of large numbers of replicated components, as the ODE problem size is insensitive to the actual population levels of the system under study. Furthermore, the ODE is given an interpretation as the fluid limit of a properly defined CTMC model when the initial population levels go to infinity. This framework allows the use of existing results which give error bounds to assess the quality of the differential approximation. The computation of performance indices such as throughput, utilisation, and average response time are interpreted deterministically as functions of the ODE solution and are related to corresponding reward structures in the Markovian setting. The differential interpretation of PEPA provides a framework that is conceptually analogous to established approximation methods in queueing networks based on meanvalue analysis, as both approaches aim at reducing the computational cost of the analysis by providing estimates for the expected values of the performance metrics of interest. The relationship between these two techniques is examined in more detail in a comparison between PEPA and the Layered Queueing Network (LQN) model. General patterns of translation of LQN elements into corresponding PEPA components are applied to a substantial case study of a distributed computer system. This model is analysed using stochastic simulation to gauge the soundness of the translation. Furthermore, it is subjected to a series of numerical tests to compare execution runtimes and accuracy of the PEPA differential analysis against the LQN mean-value approximation method. Finally, this thesis discusses the major elements concerning the development of a software toolkit, the PEPA Eclipse Plug-in, which offers a comprehensive modelling environment for PEPA, including modules for static analysis, explicit state-space exploration, numerical solution of the steady-state equilibrium of the Markov chain, stochastic simulation, the differential analysis approach herein presented, and a graphical framework for model editing and visualisation of performance evaluation results.en
dc.contributor.sponsorEU-funded project SENSORIA.en
dc.language.isoenen
dc.publisherThe University of Edinburghen
dc.relation.hasversionM. Tribastone, A. Duguid, and S. Gilmore, “The PEPA Eclipse Plug-in,” Performance Evaluation Review, vol. 36, no. 4, pp. 28–33, March 2009.en
dc.relation.hasversionM. Tribastone and S. Gilmore, “Automatic Extraction of PEPA Performance Models from UML Activity Diagrams Annotated with the MARTE Profile,” in Proceedings of the Seventh International Workshop on Software and Performance (WOSP). Princeton, New Jersey, USA: ACM, June 2008.en
dc.relation.hasversionM. Tribastone, “The PEPA Plug-in Project,” in Fourth International Conference on the Quantitative Evaluation of Systems. Edinburgh, United Kingdom: IEEE Computer Society Press, September 2007, pp. 53–54.en
dc.relation.hasversionM. Tribastone, “Relating layered queueing networks and process algebra models,” in WOSP/SIPEW ’10: Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering. New York, NY, USA: ACM, 2010, pp. 183-194.en
dc.relation.hasversionM. Tribastone and S. Gilmore, “Automatic extraction of PEPA performance models from UML activity diagrams annotated with the MARTE profile,” in Proceedingsof the 7th International Workshop on Software and Performance, WOSP, A. Avritzer, E. J. Weyuker, and C. M. Woodside, Eds. Princeton NJ, USA: ACM, 2008, pp. 67–78.en
dc.relation.hasversionM. Tribastone, “Automatic Translation of UML Sequence Diagrams into PEPA Models,” in Fifth International Conference on the Quantitative Evaluaiton of Systems (QEST 2008). Saint-Malo, France: IEEE Computer Society, 14–17 September 2008, pp. 205–214.en
dc.relation.hasversionM. Tribastone, “Differential Analysis of PEPA Models,” in Eight Workshop on Process Algebra and Stochastically Timed Activities (PASTA), Edinburgh, United Kingdom, August 2009.en
dc.subjectlarge scale systemsen
dc.subjectstate-space explosionen
dc.subjectstochastic processen
dc.subjectordinary differential equationsen
dc.subjectcontinuous-time Markov chainsen
dc.subjectCTMCen
dc.subjectLayered Queueing Networken
dc.subjectPEPA Eclipse Plug-inen
dc.titleScalable analysis of stochastic process algebra modelsen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD Doctor of Philosophyen


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