Algorithms for stationary analysis of stochastic Petri nets

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dc.contributor.advisor Balsamo, Simonetta it_IT Stojic, Ivan <1982> it_IT 2016-12-09 it_IT 2017-05-22T06:02:40Z 2017-05-22T06:02:40Z 2017-03-01 it_IT
dc.description.abstract Stochastic Petri nets (SPN) are a Markovian formalism for qualitative and quantitative analysis of discrete event dynamic systems. Among other uses, they have been used extensively in performance evaluation of telecommunication systems, computer systems and networks. Analysis of an SPN model usually requires stationary analysis of a continuous-time Markov chain (CTMC) underlying the SPN, whose state space for many practical models is too large to be analysed by direct methods. This serious drawback is shared with many other modelling formalisms and is usually referred to as state space explosion. Usually simulation can be employed to analyse such models. An alternative is to restrict the SPN formalism to product-form SPNs, a class of nets whose unnormalised stationary probability distribution can be obtained in closed form, making stationary analysis much simpler. In this thesis we present algorithms for stationary analysis of SPN models based on efficient encoding of state spaces and transition functions by multi-way decision diagrams, an efficient data structure. After a short introduction to SPNs and their stationary analysis, we start with simulation of SPNs and present an algorithm for perfect simulation in SPNs that can be used to directly obtain samples from the stationary distribution. After this, we turn to simulation of product-form SPNs and present simulation stopping criteria that exploit the product-form property. Finally, we present an algorithm for fast computation of normalizing constant, needed for the normalisation of stationary probabilities in the analysis of product-form models. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Ivan Stojić, 2017 it_IT
dc.title Algorithms for stationary analysis of stochastic Petri nets it_IT
dc.title.alternative it_IT
dc.type Doctoral Thesis it_IT Informatica it_IT Dottorato di ricerca it_IT Dipartimento di Scienze Ambientali, Informatica e Statistica it_IT
dc.description.academicyear 2015/2016, sessione 29° ciclo it_IT
dc.description.cycle 29 it_IT Focardi, Riccardo it_IT
dc.location.shelfmark D001691 it_IT
dc.location Venezia, Archivio Università Ca' Foscari, Tesi Dottorato it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 956114 it_IT
dc.format.pagenumber VIII, 68 p. it_IT
dc.subject.miur INF/01 INFORMATICA it_IT
dc.description.note it_IT it_IT Marin, Andrea <1976> it_IT
dc.provenance.upload Ivan Stojić (, 2016-12-09 it_IT
dc.provenance.plagiarycheck Maria Simonetta Balsamo (, 2017-01-19 it_IT

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