Abstract—A computer network’s performance can be improved by increasing servers, upgrading the hardware, and gaining additional bandwidth. Another important issue to increase network performance is to use an appropriate mathematical model and using that model for forecasting the network load at peak hours. We analyze a network traffic time series of Internet requests made to a workstation. This series exhibits a long-range dependence and self-similarity in large time scale and exhibits multi-fractal in small time scale. With the growing demand of using computer networks, there is increasing demand to explore new techniques for forecasting. In this paper we used the wavelet filters based on multi-resolution analysis along with the Seasonal Autoregressive Moving Average (SARIMA) models for forecasting network traffic volume. We used the Daubechies 4 (db4) wavelet filters for compression of time series and SARIMA modeling for forecasting the series. Our proposed methodology is based on the theory that most of the network traffic signals are always having the noise and unnecessary details not required for further analysis hence forecasting directly from such signals may prove computationally intensive and prone to error. The denoised and compressed signals using wavelet filters will be comparatively more smoothed and helpful for speedy and accurate forecasts. We compare our results with simple SARIMA methodology and conclude that our proposed method give better and accurate forecasts. Using wavelet based SARIMA model, we believe that with the right choice of mother wavelet, moving towards a wavelet based forecasting system would significantly improve the forecasting efficiency.

Index Terms—forecasting, network traffic, SARIMA,Wavelet.

Akhter Raza Syed is the research fellow at Department of Computer Science University of Karachi also teaching there as visiting faculty e-mail:razasyed717@msn.com.
Aqil Burney S.M. is the Chairman and Professor at Department of Computer Science University of Karachi. He is also the project director of HSFB LAN burney@uok.edu.pk
Badar Sami is the Assistant Professor at Department of Computer Science University of Karachi also he is deputy project director of HSFBLAN e-mail: badarsami@uok.edu.pk

Cite: Akhter Raza Syed, Aqil Burney S.M. and Badar Sami, "Forecasting Network Traffic Load Using Wavelet Filters and Seasonal Autoregressive Moving Average Model," International Journal  of  Computer  and  Electrical
Engineering vol. 2, no. 6, pp. 979-983, 2010.