Forecasting 802.11 Traffic using Seasonal ARIMA Model
Based on the analysis to the collected traffic from many WLAN testbed, a statistical model is proposed to predict the short-term traffic in IEEE 802.11 networks. By large numbers of differencing and sampling to the original data sequence, the season property was found and verified. Then, a time series model was given which can accurately predict the WLAN traffic: Multiple Seasonal ARIMA Model (0, 1, 1) (0, 1, 1).After iterative computation, the model was transformed into an MA model and the parameter of it has been estimated using the character of MA model Finally, a prediction to the random selected WLAN traffic has been finished through the difference function. The result of the prediction present that the employed model can short-term forecast the WLAN traffic and obtains a better result with a tiny average relative error.
IEEE 802.11 network traffic forecasting ARIMA model
Chen Chen Qingqi Pei Lv Ning
National Key Lab. of Integrated Service Networks, Xidian Univ., Xian, China, 710071
国际会议
重庆
英文
829-832
2009-12-25（万方平台首次上网日期，不代表论文的发表时间）