On Stochastic Models of Internet Traffic

The paper discusses various models of self-similar Internet traffic and techniques for estimating the intensity of Long-Range Dependence (LRD). In the experimental part real data sets collected in IITiS PAN are used together with synthetic LRD flows generated using Fractional Gaussian noise and Markov modulated Poisson processes. We are especially interested in Markov models since they can be incorporated in Markov queueing models, for which powerful analytical and numerical techniques are available.

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