Spline-Extrapolation Method in Traffic Forecasting in 5G Networks

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Ескіз

Дата

2019

Автори

Стрелковська, Ірина Вікторівна
Стрелковська, І. В.
Стрелковская, Ирина Викторовна
Strelkovska, Iryna V.
Solovska, Iryna M.
Solovska, Iryna M.
Макоганюк, Анастасія Олегівна
Makoganiuk, Anastasiya

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ISSN журналу

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Видавець

Анотація

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.

Бібліографічний опис

Strelkovska I. V. Spline-Extrapolation Method in Traffic Forecasting in 5G Networks / I. V. Strelkovska, I. N. Solovska, A.O. Makoganiuk // Journal of Telecommunications and Information Technology. - №3. - 2019. - Р. 8-16. https://doi.org/10.26636/jtit.2019.134719

Ключові слова

quality of service, self-similar traffic, spline functions, error of recover, Research Subject Categories::LAW/JURISPRUDENCE

Цитування

Strelkovska I. V. Spline-Extrapolation Method in Traffic Forecasting in 5G Networks / I. V. Strelkovska, I. N. Solovska, A.O. Makoganiuk // Journal of Telecommunications and Information Technology. - №3. - 2019. - Р. 8-16. https://doi.org/10.26636/jtit.2019.134719