Spline-Extrapolation Method in Traffic Forecasting in 5G Networks

Abstract

This paper considers the problem of predicting self-similar traffic with a significant number of pulsations and the property of long-term dependence, using various spline functions. The research work focused on the process of modeling self-similar traffic handled in a mobile network. A splineextrapolation method based on various spline functions (linear, cubic and cubic B-splines) is proposed to predict selfsimilar traffic outside the period of time in which packet data transmission occurs. Extrapolation of traffic for short- and long-term forecasts is considered. Comparison of the results of the prediction of self-similar traffic using various spline functions has shown that the accuracy of the forecast can be improved through the use of cubic B-splines. The results allow to conclude that it is advisable to use spline extrapolation in predicting self-similar traffic, thereby recommending this method for use in practice in solving traffic prediction-related problems.

A Proactive Protection of Smart Power Grids against Cyberattacks on Service Data Transfer Protocols by Computational Intelligence Methods

“…At the same time, it should be noted that there are few practical experiments aimed at studying the fractal properties of the network traffic in information and telecommunication systems. Among such works, we can single out works [ 20 , 21 , 22 ]. However, [ 20 ] considers the mobile communication traffic generated by cellular stations.…”

“…Among such works, we can single out works [ 20 , 21 , 22 ]. However, [ 20 ] considers the mobile communication traffic generated by cellular stations. The authors conclude that the properties of self-similarity are inherent not only in computer and telecommunications networks, but also in the radio waves on which cellular stations operate.…”

An Approach to Detecting Cyber Attacks against Smart Power Grids Based on the Analysis of Network Traffic Self-Similarity

“…It should be noted that there are few practical experiments aimed at studying the fractal properties of network traffic in telecommunication systems. Among this kind of work, one can single out the papers [15][16][17]. However, in [15], traffic is considered not in information and telecommunication networks, but in radio waves transmitted by cellular stations.…”

“…However, in [15], traffic is considered not in information and telecommunication networks, but in radio waves transmitted by cellular stations. In addition, researchers come to the conclusion that movement is self-similar, often relying solely on visual signs [16,17]. They look for similar areas on the chart, passing them off as self-similar processes.…”

“…Such a test is called the ADF test. The need to include lags of the first differences is due to the fact that the process may not be autoregression of the first, but of a higher order [17][18][19].…”