Correlational and distributional effects in network traffic models

Simulation studies are used to evaluate the impact of the distributional and correlational characteristics of traffic arrival processes on the performance of network routing elements. It is shown that synthetic traffic models that capture only the distributional or the correlational characteristics of real workloads can yield substantially optimistic predictions of queue lengths and drop rate. A new technique for generating synthetic arrival streams is proposed and evaluated. Arrival streams are generated by the widely-used method of sampling from a target distribution. However, the uniform stream used in the sampling is itself derived from fractional Gaussian noise. The resulting synthetic streams are shown to have sample autocorrelation functions that are consistent with long-range dependence and to provide measurably better performance estimates than standard distribution-based and FGN-based techniques