Abstract

The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using queueing Petri nets (QPNs), one can integrate both hardware and software aspects of system behavior into the same model. This lends itself very well to modeling distributed component-based systems, such as modern e-business applications. However, currently available tools and techniques for QPN analysis suffer the state space explosion problem, imposing a limit on the size of the models that are tractable. In this paper, we present SimQPN—a simulation tool for QPNs that provides an alternative approach to analyze QPN models, circumventing the state space explosion problem. In doing this, we propose a methodology for analyzing QPN models by means of discrete event simulation. The methodology shows how to simulate QPN models and analyze the output data from simulation runs. We validate our approach by applying it to study several different QPN models, ranging from simple models to models of realistic systems. The performance of point and interval estimators implemented in SimQPN is subjected to a rigorous experimental analysis.

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