Chaotic forecast of the signaling traffic in NGN

Traffic forecast is of great significance in the research field of resource allocation and congestion control. Based on the chaotic characteristics of the signaling traffic in the next generation network (NGN), a weighted average maximum Lyapunov exponent forecast (WAMLEF) chaotic forecast method is provided. The simulation results demonstrate that the average error of the proposed method is 8% less than that of the maximum Lyapunouv exponent chaotic forecast method. The presented method has better prediction performance and establishes foundation for signaling network resource allocation and traffic flow control.