WNN-based NGN traffic prediction

Abstract

In this paper we introduce a methodology to predict IP traffic in IP-based next generation network (NGN). By using Netflow traffic collecting technology, we've collected some traffic data for the analysis from an NGN operator. To build wavelet basis neural network (NN), we replace Sigmoid function with the wavelet in NN, and use wavelet multiresolution analysis method to decompose the traffic signal and then employ the decomposed component sequences to train the NN. By using the methods, we build a NGN traffic prediction model by which to predict one day's traffic. The experimental results show that the traffic prediction method of wavelet NN (WNN) is more accurate than that without using wavelet in the NGN traffic forecasting.