Network traffic forecasting based on the canonical expansion of a random process

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.131471

Keywords:

network traffic, forecasting control, random process, canonical decomposition of a random process

Abstract

We studied the problem of forecasting network traffic in TCP/IP networks based on statistical observational data. We determined that existing protocols (SNMP, RMON) do not provide long-term forecasting, which is necessary for network upgrades. Regression methods (AR, ARMA, ARIMA, SARIMA), which are the basis of protocols, use only a sequence of values of forecasted series, which makes long-term forecasting impossible. We made a conclusion that there is no universal effective method for forecasting time sequences that describe traffic of a computer network.

We developed the model of a forecast of network traffic taking into account features of accumulation of statistical data: presence of a priori trajectories, a posteriori character of forecasting, finiteness of variance. We applied the apparatus of the canonical expansion of a random process, taking into account heterogeneity of traffic. We developed a mathematical apparatus to solve the problem of extrapolation of implementation; we obtained expressions for the estimation of an extrapolation error, and expressions for the reconstruction of a posteriori random process based on modeling. We took into account accuracy of a priori measurements, which makes it possible to use this model in networks with a minimum of diagnostic data. It provides accurate determination of parameters of a random process at control points and the minimum standard approximation error in the intervals between these points.

Application of the proposed method based on the canonical decomposition of random processes provides a solution to the problem of long-term forecasting of network traffic. A comparative analysis of forecasting methods indicates that the method of canonical decomposition of a random process comes close to intelligent forecasting methods.

Author Biographies

Vitalii Savchenko, Information Security Institute State University of Telecommunications Solomianska str., 7, Kyiv, Ukraine, 03110

Doctor of Technical Sciences, Senior Researcher

Department of Information and cyber security

Oleksander Matsko, Institute operational support and logistics Ivan Chernyakhovsky National Defense University of Ukraine Povitroflotsky ave., 28, Kyiv, Ukraine, 03049

PhD, Associate professor

Oleh Vorobiov, Institute operational support and logistics Ivan Chernyakhovsky National Defense University of Ukraine Povitroflotsky ave., 28, Kyiv, Ukraine, 03049

Doctor of Technical Sciences, Professor

Yaroslav Kizyak, Institute operational support and logistics Ivan Chernyakhovsky National Defense University of Ukraine Povitroflotsky ave., 28, Kyiv, Ukraine, 03049

PhD

Scientific research laboratory

Larysa Kriuchkova, Information Security Institute State University of Telecommunications Solomianska str., 7, Kyiv, Ukraine, 03110

Doctor of Technical Sciences, Associate professor

Department of Information and cyber security

Yurii Tikhonov, Information Security Institute Department of Information and cyber security Solomianska str., 7, Kyiv, Ukraine, 03110

PhD, Associate professor

Department of Information and cyber security

Andrei Kotenko, Information Security Institute State University of Telecommunications Solomianska str., 7, Kyiv, Ukraine, 03110

PhD

Department of Information and cyber security

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Published

2018-05-18

How to Cite

Savchenko, V., Matsko, O., Vorobiov, O., Kizyak, Y., Kriuchkova, L., Tikhonov, Y., & Kotenko, A. (2018). Network traffic forecasting based on the canonical expansion of a random process. Eastern-European Journal of Enterprise Technologies, 3(2 (93), 33–41. https://doi.org/10.15587/1729-4061.2018.131471