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Title: Spline-Extrapolation Method in Traffic Forecasting in 5G Networks, Journal of Telecommunications and Information Technology, 2019, nr 3

Creator:

Makoganiuk, Anastasiya ; Solovskaya, Irina ; Strelkovskaya, Irina

Date:

2019, nr 3

Resource Type:

artykuł

Description:

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.

Publisher:

National Institute of Telecommunications

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2100

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

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

Object collections:

Last modified:

Oct 23, 2019

In our library since:

Oct 23, 2019

Number of object content hits:

139

All available object's versions:

https://bc.itl.waw.pl/publication/2390

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Edition name Date
Strelkovskaya, Irina; Solovskaya, Irina; Makoganiuk, Anastasiya, Spline-Extrapolation Method in Traffic Forecasting in 5G Networks, Journal of Telecommunications and Information Technology, 2019, nr 3 Oct 23, 2019

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