In: MASCOTS'93 International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, San Diego, CA, pages 367-372. 1993.
Abstract: In this paper we describe the modeling of complex systems using stochastic reward nets (SRNs) which are stochastic Petri nets (SPNs) augmented with the ability to specify output measures as reward based functions. The solution of the SRNs involves generation and solution of the corresponding Markov reward model. Several structural extensions to SPNs, including marking dependency, variable cardinality arcs, assertions and guards which are useful in modeling the complex behavior of systems, are described. The use of SRNs in modeling complex systems is illustrated through some interesting examples. We mention the use of the Stochastic Petri Net Package (SPNP) for the description and solution of SRN models
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