Application of non-linear time series model GARCH in network traffic forecast

HUANG Shizhong, LIU Yuan

1. School of Digital Media, Jiangnan University, Wuxi, Jiangsu 214122, China
• Online:2014-03-01 Published:2015-05-12

GARCH非线性时间序列模型的网络流量预测

1. 江南大学 数字媒体学院，江苏 无锡 214122

Abstract: Forecasting of network traffic plays a significant role in many domains such as congestion control, network management and diagnose, and router design. In accordance with modern network, traditional Auto Regressive Moving Average（ARMA） model fails to describe the characteristic of network traffic very well. Therefore, Generalized Auto Regressive Conditional Heteroskedasticity（GARCH） model is studied for network traffic. The simulation shows that GARCH model is well fitted on the real data of network traffic. Meanwhile, the accuracy of the forecast based on the model is much better than that of ARMA model.