SIMULATION OF LARGE-SCALE NETWORKS USING SSF

Some applications of simulation require that the model state he advanced in simulation time faster than the wall-clock time advances as the simulation executes. This faster rhan real-rime requirement is crucial, for instance, when a simu-lation is used as part of a real-time control system, working through the consequences of contemplated control actions, in order to identify feasible (or even optimal) decisions. This paper considers the issue of faster than real-time sim-ulation of very large communication networks, and how this is accomplished using our implementation (in C++) of the Scalable Simulation Framework (SSF). Our tool (called ISSF) uses hierarchical levels of abstraction, and parallelism, to achieve speedups of nearly four orders of magnitude, enabling real-time execution rates on large network models. We quantify the effects that choice of hierarchical abstrac-tion has on the simulation time advance rate, and show empirically how changing the abstraction mix affects the execution rate on a large network example.