KOLMOGOROV-WIENER FILTER FOR CONTINUOUS TRAFFIC PREDICTION IN THE GFSD MODEL

Authors

  • V. N. Gorev Dnipro University of Technology, Dnipro, Ukraine , Ukraine
  • A. Yu. Gusev Dnipro University of Technology, Dnipro, Ukraine , Ukraine
  • V. I. Korniienko Dnipro University of Technology, Dnipro, Ukraine, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2022-3-3

Keywords:

Kolmogorov-Wiener filter weight function, continuous telecommunication traffic, truncated polynomial expansion method, GFSD model, Chebyshev polynomials of the first kind.

Abstract

Context. We investigate the Kolmogorov-Wiener filter weight function for the prediction of continuous stationary telecommunication traffic in the GFSD (Gaussian fractional sum-difference) model.

Objective. The aim of the work is to obtain an approximate solution for the corresponding weight function and to illustrate the convergence of the truncated polynomial expansion method used in this paper.

Method. The truncated polynomial expansion method is used for the obtaining of an approximate solution for the KolmogorovWiener weight function under consideration. In this paper we used the corresponding method on the basis of the Chebyshev polynomials of the first kind orthogonal on the time interval on which the filter input data are given. It is expected that the results based on other polynomial sets will be similar to the results obtained in this paper.

Results. The weight function is investigated in the approximations up to the eighteen-polynomial one. It is shown that approximations of rather large numbers of polynomials lead to a good coincidence of the left-hand side and the right-hand side of the Wiener-Hopf integral equation. The quality of the coincidence is illustrated by the calculation of the corresponding MAPE errors.

Conclusions. The paper is devoted to the theoretical construction of the Kolmogorov-Wiener filter for the prediction of continuous stationary telecommunication traffic in the GFSD model. The traffic correlation function in the framework of the GFSD model is a positively defined one, which guarantees the convergence of the truncated polynomial expansion method. The corresponding weight function is obtained in the approximations up to the eighteen-polynomial one. The convergence of the method is illustrated by the calculation of the MAPE errors of misalignment of the left-hand side and the right-hand side of the Wiener-Hopf integral equation under consideration. The results of the paper may be applied to practical traffic prediction in telecommunication systems with data packet transfer.

Author Biographies

V. N. Gorev, Dnipro University of Technology, Dnipro, Ukraine

PhD, Assoсiate Professor of the Department of Information Security and Telecommunications

A. Yu. Gusev, Dnipro University of Technology, Dnipro, Ukraine

Dr. Sc., Professor, Head of the Department of Information Security and Telecommunications

V. I. Korniienko, Dnipro University of Technology, Dnipro, Ukraine

Dr. Sc., Professor, Head of the Department of Information Security and Telecommunications

References

Liu J. X., Jia Z. H. Telecommunication Traffic Prediction Based on Improved LSSVM, International Journal of Pattern Recognition and Artificial Intelligence, 2018, Vol. 32, No. 3, 1850007 (16 pages). DOI: 10.1142/S0218001418500076

Iqbal M. F., Zahid M., Habib D. et al. Efficient Prediction of Network Traffic for Real-Time Applications, Journal of Computer Networks and Communications, 2019, Vol. 2019, 4067135 (11 pages). DOI: 10.1155/2019/4067135.

Katris C., Daskalaki S. // Comparing forecasting approaches for Internet traffic, Expert Systems with Applications, 2015, Vol. 42, Issue 21, pp. 8172–8183. DOI: 10.1016/j.eswa.2015.06.029.

Bilgil H. New grey forecasting model with its application and computer code, AIMS Mathematics, 2021, Vol. 6, Issue 2, pp. 1497–1514. DOI: 10.3934/math.2021091

Al-Azzeh J. S., Al Hadidi M., Odarchenko R. et al. Analysis of Self-Similar Traffic Models in Computer Networks, International Review on Modelling and Simulations, 2017, Vol. 10, No. 5, pp. 328–336. DOI: 10.15866/iremos.v10i5.12009

Gorev V. N., Gusev A. Yu., Korniienko V. I. Polynomial solutions for the Kolmogorov-Wiener filter weight function for fractal processes, Radio Electronics, Computer Science, Control, 2019, No. 2, pp. 44–52. DOI: 10.15588/1607-32742019-2-5

Gorev V. N., Gusev A. Yu., Korniienko V. I. Approximate solutions for the Kolmogorov-Wiener filter weight function for continuous fractional Gaussian noise, Radio Electronics, Computer Science, Control, 2021, No. 1, pp. 29–35. DOI: 10.15588/1607-3274-2021-1-3

Gorev V. N., Gusev A., Korniienko V., Aleksieiev M., Vorobiyenko P., Ilchenko M., Strelkovska I. KolmogorovWiener Filter Weight Function for Stationary Traffic Forecasting: Polynomial and Trigonometric Solutions, Current Trends in Communication and Information Technologies. Cham, Springer, 2021, Chapter 7, pp. 111–129. DOI: 10.1007/978-3-030-76343-5_7

Anderson D., Cleveland W. S., Xi B. Multifractal and Gaussian fractional sum–difference models for Internet traffic, Performance Evaluation, 2017, Vol. 107, pp. 1–33. DOI: 10.1016/j.peva.2016.11.001

Miller S., Childers D. Probability and Random Processes With Applications to Signal Processing and Communications. Second edition. Amsterdam, Academic Press, 2012, 598 p. DOI: 10.1016/B978-0-12-386981-4.50001-1

Polyanin A. D., Manzhirov A. V. Handbook of integral equations. Second edition. New York, Chapman and Hall, 2008, 1144 p. DOI: 10.1201/9781420010558

Gradshteyn I. S., Ryzhik I. M., Geronimus Yu. V. et al. Table of Integrals, Series, and Products. Eights edition. Amsterdam, Academic Press, 2014, 1184 p. DOI: 10.1016/C2010-0-64839-5

Downloads

Published

2022-10-01

How to Cite

Gorev, V. N., Gusev, A. Y., & Korniienko, V. I. (2022). KOLMOGOROV-WIENER FILTER FOR CONTINUOUS TRAFFIC PREDICTION IN THE GFSD MODEL . Radio Electronics, Computer Science, Control, (3), 31. https://doi.org/10.15588/1607-3274-2022-3-3

Issue

Section

Mathematical and computer modelling