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Advanced Models and Algorithms for Self–Similar IP Network Traffic Simulation and Performance Analysis
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Journal of Electrical Engineering
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2010
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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 generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
Citation
Radev, D., and Lokshina, I. (2010). Advanced Models and Algorithms for Self-Similar Network Traffic Simulation and Performance Analysis. Journal of Electrical Engineering (JEE)/the Institute of Electrical and Electronics Engineers (IEEE); online: Wersita, Warsaw - Central European Science Publishers, 61(6), p. 341-349