An ARIMA model for forecasting a values of network traffic

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 and self-similarity in the large time scale. In this paper the model ARIMA with minimal amount of parameters has been selected to accurate the traffic prediction. Also the procedure of the estimating of the parameters of the ARIMA model has been exhibited and compared the estimations of accurate the traffic prediction for the getting models.