Combining queueing networks and generalized stochastic Petri nets for the solution of complex models of system behavior

A technique is presented whereby queueing network models and generalized stochastic Petri nets are combined in such a way as to exploit the best features of both modeling techniques. The resulting hierarchical modeling approach is useful in the solution of complex models of system behavior. The authors have chosen two examples from the recent literature to illustrate the power and scope of this technique. They also demonstrate how folding of the generalized stochastic Petri net models for these two examples is useful in obtaining efficiently solvable, approximate models (bounding models)