А METHOD OF SIMULATION OF COMPUTER NETWORK TRAFFIC WITH FRACTAL PROPERTIES
DOI:
https://doi.org/10.26906/SUNZ.2022.4.075Keywords:
computer networks, network traffic, fractal dimension, Markov processes, simulation modeling, computer simulation modelAbstract
The goal of this work is to create a method of simulating computer network traffic with fractal properties for testing network algorithms and protocols. The object of research is the process of simulation modeling of network traffic. The subject of research is the methods and algorithms for modeling time series with fractal properties. Nowadays, mathematical models of self-similar time series are used for the mathematical description of telecommunication processes. In most cases, for selfsimilar traffic, predicting parameters based on the quality of QoS service, analytical expressions cannot be constructed, or such transformations can be constructed for too specific situations, so mostly analytical calculations are impractical. For this reason, to determine the main indicators of the quality of service, such as jitter, delay, average number of failures, and others, simulation modeling using self-similar traffic generators is used. This leads to the need for computationally simple generators of self –similar traffic with controlled fractal properties, which would give numerical sequences with properties as close as possible to the properties of the real traffic of the telecommunication network under investigation. In this paper, a method of simulation modeling of computer network traffic with fractal properties is proposed. The theory of fractal analysis and the theory of Markov processes were used to generate traffic. This method can be part of a software simulation model of a computer network, which in turn can be used for testing network algorithms and protocols. Also a developed simulation model of network traffic is planned to be used in the future for testing the quality of methods for determining the fractal dimension of time series, as well as for forecas ting the load of network devices in computer networks.Downloads
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