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Analysis of Self-Similar Traffic Models in Computer Networks

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The growth of society digitalization increases the requirements for data transmission productivity of the information telecommunication networks. Traffic in these networks is self-similar. For its modeling a number of fractal traffic imitation models were developed. However, the modern studies show that the traffic characteristics may change in the wide networks and be dependent of big number of parameters and settings of real networks, protocol and transmitted information’s characteristics, and users’ behavior. So the main aim of the paper was an investigation of modern traffic models to choose the best of them for modern computer networks with different characteristics traffic flow modeling and creation of computer models for generating self-similar traffic in MathCAD. It allows to investigate state of computer networks with different traffic flows conditions, behavior of connected network devices, queue, processing order as good for traditional computer networks and software defined networks with the help of wide-spread MathCAD software.
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Traffic; Models of Network Traffic; Fractional Brownian Motion; Self-Similarity; RMD Algorithm

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