The Evolution of Stochastic Petri Nets
نویسندگان
چکیده
Analytical modeling is a crucial part in the analysis and design of computer systems. Stochastic Petri Nets represent a powerful tool, widely used for dependability, performance and performability modeling. Many structural and stochastic extensions have been proposed so as to increase their modeling power. In this paper we review the main structural and stochastic extensions of Petri nets, by providing an updated treatment of the theoretical background and the possible areas of application. In particular, we focus our attention on Stochastic and Generalized Stochastic Petri nets (SPN and GSPN), Stochastic Reward Nets (SRN) and on non-Markovian Petri nets such as Markov Regenerative Stochastic Petri Nets (MRSPN). Fluid Stochastic Petri Nets (FSPN) are discussed.
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