Comparison research on of prediction methods for WLAN traffic
无线局域网业务流预报方法比较

A number of traffic prediction methods based on time series as Artificial Neural Networks (ANN) and wavelet were briefly described. Their performances were compared using three actual wireless network traffic traces. Wireless traffic with time series model, artificial neural network, and wavelet-base method were separately predicted. The experimental results show the significant advantages of the ANN technique and AutoRegression Integrated Moving Average (ARIMA) predictor performs relatively the worst.