Izabella Lokshina

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The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence(More)
The paper recommends an approach to estimate effectively the probability of buffer overflow in high-speed communication networks, capable of carrying diverse traffic, including self-similar teletraffic, and supporting diverse levels of quality of service. Simulations with stochastic, long-range dependent self-similar traffic source models are conducted. A(More)