Generalized Stochastic Petri Nets (GSPNs) are presented and are applied to the performance evaluation of multiprocessor systems. GSPNs are derived from standard Petri nets by partitioning the set of transitions into two subsets comprising timed and immediate transitions. An exponentially distributed random firing time is associated with each timed transition, whereas immediate transitions fire in zero time. It is shown that GSPNs are equivalent to continuous-time stochastic processes, and solution methods for the derivation of the steady state probability distribution are presented. Examples of application of GSPN models to the performance evaluation of multiprocessor systems show the usefulness and the effectiveness of this modeling tool.

A Class of Generalized Stochastic Petri Nets for the Performance Analysis of Multiprocessor Systems

BALBO, Gianfranco;
1984-01-01

Abstract

Generalized Stochastic Petri Nets (GSPNs) are presented and are applied to the performance evaluation of multiprocessor systems. GSPNs are derived from standard Petri nets by partitioning the set of transitions into two subsets comprising timed and immediate transitions. An exponentially distributed random firing time is associated with each timed transition, whereas immediate transitions fire in zero time. It is shown that GSPNs are equivalent to continuous-time stochastic processes, and solution methods for the derivation of the steady state probability distribution are presented. Examples of application of GSPN models to the performance evaluation of multiprocessor systems show the usefulness and the effectiveness of this modeling tool.
1984
2 (2) May 1984
93
122
Petri Nets; Generalized Petri Nets; Markov Chain; Performance Evaluation; Modelling Formalism; Modelling
M. Ajmone Marsan; G. Balbo; G. Conte
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1949
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