Network traffic multi-step prediction based on chaos theory and improved echo state network - Zhong-da TIAN; Shu-jiang LI; Yan-hong WANG; Xiang-dong WANG (Tongxin xuebao)
Network traffic prediction was an important problem of network management and network congestion control.In order to solve this problem,a network traffic prediction method based on chaos theory and improved echo state net-work was proposed.Firstly,network traffic sample with differe time scale were analyzed by 0-1 test algorithm for chaos and maximum Lyapunov exponent,the calculation results show that the network traff has chaotic characteristics in different time scale.The phase space reconstruction technique was introduced for the prediction of network traffic,the delay time was determined through the C-C method,the embedding dimension was determined through the G-P algo-rithm.Network traffic time series was processed with phase space reconstruction,the multi-step prediction of network traffic was achieved by an improved echo state network.In order to improve the prediction precision,the key dynamic reservoir and prediction parameters of echo state network were optimized by an improved harmony search algorithm.Through the simulation on public and actual network traffic data,the results verify the proposed prediction method has higher prediction accuracy and smaller prediction error.