Applying Multiple Residual Error Gray Forecast to Restrain Endpoints Effect in HHT of Network Traffic

Studying the features of network traffic is a necessary method in many applications such as managing and monitoring the network, detecting network attack etc. Due to the non-stationary and random characteristics of the traffic signal, Hilbert-Huang Transformation (HHT) is an effective method in signal processing. However, endpoints effect comes subsequently in HHT. In this particular case, the paper introduces a multiple residual error gray forecast method to realize data continuation so as to inhibiting endpoints effect in applying HHT to network traffic signal. Experimental results show that this method can effectively restrain the endpoint divergence phenomenon in applying HHT to network traffic signal, but it is not applicable to deterministic signals.