Abstract
The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose a new network traffic prediction model based on non-linear time series ARIMA/GARCH. This model combines linear time series ARIMA model with non-linear GARCH model. We provide a parameters estimation procedure for our proposed ARIMA/GARCH model. We then evaluate a scheme for our models’ prediction. We show that our model can capture prominent traffic characteristics, not only in large time scale but also in small time scale. Compare with existing FARIMA model, our model have better prediction accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
M. Stemm, S. Seshan and R.H. Katz, “A network measurement architecture for adaptive applications”, Proceedings of INFOCOM 2000, vol.1, pp.285–294.
V. Jacobson, “Congestion avoidance and control”, Proceedings of the ACM SIGCOMM 1988 Symposium, pp.314–329.
S. Jamin, P. Danzig, S. Schenker and L. Zhang, “A measurement-based admission control algorithm for integrated services packet networks”, Proceedings of ACM SIGCOMM’95, pp.56–70.
M. Kim and B. Noble, “Mobile network estimation”, Proceedings of the Seventh Annual International Conference on Mobile Computing and Networking, pp.298–309.
S.F. Bush, “Active virtual network management prediction”, Proceedings of the 13 th Workshop on Parallel and Distributed Simulation (PADS’99), pp. 182–192.
A. Sang and S. Li, “A predictability analysis of network traffic”, Computer networks, vol. 39, pp. 329–345, 2002.
A. Adas, “Traffic models in broadband networks”, IEEE Comm. Mag., vol. 35, pp. 82–89. July 1997.
W.E. Leland, M.S. Taqqu, W. Willinger and D.V. Wilson, “On the self-similar nature of Ethernet traffic (Extended Version)”, IEEE/ACM Trans. Net., vol. 2, no. 1, pp. 1–15, Feb 1994.
Y. Shu, Z. Jin, L. Zhang, L. Wang and O.W.W. Yang, “Traffic prediction using FARIMA models”, ICC’99, vol.2, pp. 891–895, 1999.
M. Corradi, R.G. Garroppo, S. Giordano and M. Pagano, “Analysis of f-ARIMA processes in the modeling of broadband traffic”, ICC’01, vol.3, pp.964–968, 2001.
Rudolf H. Riedi, Vinay J. Ribeiro, Matthew S. Crouse, Richard G. Baraniuk, “Network Traffic Modeling Using a Multifractal Wavelet Model,” DSPCS’99, Perth, 1999.
C. You and K. Chandra, “Time series models for Interent data traffic”, Proceedings of the 24 th Conference on Local Computer Networks (LCN 99), pp. 164–171.
Bollerslev, T., R.Y. Chou, and K.F. Kroner, “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence,” Journal of Econometrics, Vol.52, 1992.
C. Gourieroux, “ARCH Models and Financial Applications”, Springer Series in Statistics, Springer-Verlag New York, 1997.
T. Nakatsuma and H. Tsurumi, “ARMA-GARCH models: Bayes Estimation Versus MLE, and Bayes Non-stationary Test”, department working papers with number 199619, department of Economics, Retgurs University, 1996.
P. Brockwell and R. Davis, “Introduction to Time Series and Forecasting”, Springer, 1996.
S. Makridakis, S.C. Wheelwright and V. McGee, “Forecasting Methods and Applications”, second edition, Wiley, 1983.
http://ita.ee.lbl.gov/html/contrib/LBL-TCP-3.html
Y. Gao, G. He and J.C. Hou, “On Leveraging traffic predictability in active queue management”, Proc. IEEE INFOCOM 2002, June 2002.
Box, G.E.P., G.M. Jenkins, and G.C. Reinsel, “Time Series Analysis: Forecasting and Control”, 3rd edition, Prentice Hall, 1994.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Science+Business Media, LLC
About this paper
Cite this paper
Zhou, B., He, D., Sun, Z. (2006). Traffic Modeling and Prediction using ARIMA/GARCH Model. In: Nejat Ince, A., Topuz, E. (eds) Modeling and Simulation Tools for Emerging Telecommunication Networks. Springer, Boston, MA . https://doi.org/10.1007/0-387-34167-6_5
Download citation
DOI: https://doi.org/10.1007/0-387-34167-6_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-32921-5
Online ISBN: 978-0-387-34167-5
eBook Packages: Computer ScienceComputer Science (R0)