Symbolic techniques for the performance analysis of generalised stochastic petri nets

dc.contributor.advisorKritzinger, Pieter Sen_ZA
dc.contributor.authorDavies, Ianen_ZA
dc.date.accessioned2014-08-13T19:28:41Z
dc.date.available2014-08-13T19:28:41Z
dc.date.issued2001en_ZA
dc.descriptionIncludes abstract Thesis (M.Sc. (Computer Science))-- University of Cape Town, 2001.en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractBinary Decision Diagrams (BDDs) have been successfully used in sequential circuit theory, VLSI, and model checking. They form a highly memory efficient canonical representation of a Boolean function. In this dissertation, following on the success of BDDs in other fields, we investiage the applicability of symbolic techniques in the performance analysis of timed transition systems, particularly those of Generalised Stochastic Petri Nets (GSPNs). We make use of symbolic methods, where states are represented implicitly rather than explicitly, primarily to conserve memory during the state space exploration process - a necessary step in the performance analysis pipeline. We have investigated the use of BDDs in two different ways. The first, our own novel technique, allows the user to effectively place an upper bound on the amount of memory to use during state space exploration. The second makes use of transition to find the successor states at each level of the state graph. Both of these techniques rely on a novel and efficient GSPN to BDD encoding function that we have derived.en_ZA
dc.identifier.apacitationDavies, I. (2001). <i>Symbolic techniques for the performance analysis of generalised stochastic petri nets</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/6389en_ZA
dc.identifier.chicagocitationDavies, Ian. <i>"Symbolic techniques for the performance analysis of generalised stochastic petri nets."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2001. http://hdl.handle.net/11427/6389en_ZA
dc.identifier.citationDavies, I. 2001. Symbolic techniques for the performance analysis of generalised stochastic petri nets. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Davies, Ian AB - Binary Decision Diagrams (BDDs) have been successfully used in sequential circuit theory, VLSI, and model checking. They form a highly memory efficient canonical representation of a Boolean function. In this dissertation, following on the success of BDDs in other fields, we investiage the applicability of symbolic techniques in the performance analysis of timed transition systems, particularly those of Generalised Stochastic Petri Nets (GSPNs). We make use of symbolic methods, where states are represented implicitly rather than explicitly, primarily to conserve memory during the state space exploration process - a necessary step in the performance analysis pipeline. We have investigated the use of BDDs in two different ways. The first, our own novel technique, allows the user to effectively place an upper bound on the amount of memory to use during state space exploration. The second makes use of transition to find the successor states at each level of the state graph. Both of these techniques rely on a novel and efficient GSPN to BDD encoding function that we have derived. DA - 2001 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2001 T1 - Symbolic techniques for the performance analysis of generalised stochastic petri nets TI - Symbolic techniques for the performance analysis of generalised stochastic petri nets UR - http://hdl.handle.net/11427/6389 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/6389
dc.identifier.vancouvercitationDavies I. Symbolic techniques for the performance analysis of generalised stochastic petri nets. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2001 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/6389en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.titleSymbolic techniques for the performance analysis of generalised stochastic petri netsen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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