Spline-Extrapolation Method in Traffic Forecasting in 5G Networks

Authors

  • Irina Strelkovskaya State University of Intelligent Technologies and Telecommunications image/svg+xml
  • Irina Solovskaya State University of Intelligent Technologies and Telecommunications image/svg+xml
  • Anastasiya Makoganiuk State University of Intelligent Technologies and Telecommunications image/svg+xml

DOI:

https://doi.org/10.26636/jtit.2019.134719

Keywords:

quality of service, self-similar traffic, spline functions, error of recovery

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.

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Submitted

2023-06-10

Published

2019-09-30

Issue

No. 3 (2019)

Section

ARTICLES FROM THIS ISSUE

License

Copyright (c) 2019 Journal of Telecommunications and Information Technology

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
I. Strelkovskaya, I. Solovskaya, and A. Makoganiuk, “Spline-Extrapolation Method in Traffic Forecasting in 5G Networks”, JTIT, vol. 77, no. 3, pp. 8–16, Sep. 2019, doi: 10.26636/jtit.2019.134719.