Efficient simulation of ATM networks with accurate end-to-end delay statistics

We present a technique to enable the efficient simulation of large scale ATM networks, while preserving the accuracy of the end-to-end delay statistics. Our approach uses on-the-fly aggregation by observing traffic at monitoring points, then substituting an aggregate model, when appropriate. We focus in particular on the end-to-end delay distribution, given the importance of this distribution for continuous media. We find that our methods are able to achieve speedup of one order of magnitude, while maintaining accuracy within 5% of the unaggregated simulation. These results are observed in both a series of multiplexers and a 100-switch wide-area ATM topology.