Open AccessSpline-Extrapolation Method in Traffic Forecasting in 5G Networks
Author(s) -
Irina Strelkovskaya,
Irina Solovskaya,
Anastasiya Makoganiuk
Publication year - 2019
Publication title -
journal of telecommunications and information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.151
H-Index - 12
eISSN - 1899-8852
pISSN - 1509-4553
DOI - 10.26636/jtit.2019.134719
Subject(s) - extrapolation , spline (mechanical) , computer science , b spline , mathematics , smoothing spline , thin plate spline , algorithm , spline interpolation , statistics , mathematical analysis , physics , computer vision , bilinear interpolation , thermodynamics
This paper considers the problem of predicting self-similar trac with a signicant 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 trac handled in a mobile network. A splineextrapolation method based on various spline functions (linear, cubic and cubic B-splines) is proposed to predict selfsimilar trac outside the period of time in which packet data transmission occurs. Extrapolation of trac for short- and long-term forecasts is considered. Comparison of the results of the prediction of self-similar trac 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 trac, thereby recommending this method for use in practice in solving trac prediction-related problems.