Published May 25, 2023 | Version v1
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A Method of Routing of Fractal-like Traffic with Prediction of Router Load for Reduce the Probability of Network Packet Loss

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In this paper, a method for routing fractal-like traffic in computer networks was proposed. This method uses the prediction of router load by analyzing the fractal dimension of network traffic to reduce the probability of packet loss. It takes into account the predicted router load as one of the metrics for determining the shortest packet transmission routes in a computer network. Additionally, a computer simulation model of a computer network based on complex network theory, Markov processes, and fractal time series was created. This computer simulation model allows the generation of a computer network structure and simulates traffic movement between network devices for testing routing algorithms. A series of experiments on the developed computer network model to determine the quality of the proposed routing method and compare it with other methods were conducted. During the analytical research and experiments, the impact of different fractal dimensions of traffic on the probability of packet loss and, consequently, on the quality of service at high traffic intensity was investigated. And it also investigated whether the proposed routing method allows for the reduction of the number of lost network packets. Analyzing the results of the experiments, the following conclusions can be drawn. The fewest lost packets were when the process was random or had weakly expressed trends, which was modeled in the experiment by traffic with the fractal dimension equal to 1.5. Persistent and anti-persistent processes (those with memory) cause more packet loss for the same traffic intensity and the same maximum number of packets generated per device per unit of time. Moreover, the anti-persistent processes modeled in the experiment by traffic with the fractal dimension equal to 1.75 cause significantly greater losses than persistent processes modeled with the fractal dimension of 1.25. Also, the results of the experiments showed that the proposed traffic routing method allows for a significantly reduced number of lost packets compared to the existing method without prediction based on fractal traffic analysis.

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