Based on Chaos Theory's Network Traffic Flow Prediction of Time Series Research

Abstract

For more accurate network traffic time series prediction, can effectively relieve network overload and network congestion and other phenomena, but the traditional model of network traffic prediction is limited. In this paper, a chaotic time series prediction method of network traffic, first carried out reconstruction of phase space method using mutual information and false near the point method to determine the delay time and embedding dimension, with a small amount of data the maximum Lyapunov index method, thus proving that the network traffic chaotic time series, and establish the corresponding model, made a prediction of its success, the simulation results show that the method has high accuracy.