A tunable discrete traffic generator based on a hierarchical scheme of Bernoulli sources

In this paper we present an efficient method for the generation of a discrete series of traffic. The method is based on a superposition of hierarchical Bernoulli sources and generates non-Gaussian distributions. This way self-similar traffic can be generated with an arbitrary combination of Hurst parameter, variance and mean. The method is fully parameterized before generating the trace, which avoids the need for post-processing. Contrary to other methods, the method also allows calculating the trace point by point. The described hierarchical scheme offers a generic framework for fitting the variance-time behavior and can be combined with other stochastic sources.