Chaotic Control of Network Traffic

A method of chaotic control on network traffic is presented. By this method, the chaotic network traffic can be controlled to a pre-assigned equilibrium point according to chaotic prediction and the largest Lyapunov exponent of
the traffic on congested link is reduced, thereby the probability of traffic burst and network congestion can be reduced. Numerical examples show that this method is effective.     

Network traffic prediction by a wavelet-based combined model

Network traffic prediction models can be grouped into two types, single models and combined ones. Combined models integrate several single models and thus can improve prediction accuracy. Based on wavelet transform, grey theory, and chaos theory, this paper proposes a novel combined model, wavelet--grey--chaos (WGC), for network traffic prediction. In the WGC model, we develop a time series decomposition method without the boundary problem by modifying the standard \grave\rm a trous algorithm, decompose the network traffic into two parts, the residual part and the burst part to alleviate the accumulated error problem, and employ the grey model GM(1,1) and chaos model to predict the residual part and the burst part respectively. Simulation results on real network traffic show that the WGC model does improve prediction accuracy.     

TCP-RED离散反馈系统中的边界碰撞分岔及混沌控制

结合范式方法对传输控制协议和随机早期检测（TCP-RED）离散反馈系统中出现的不同种类的边界碰撞分岔现象进行了分析.随着系统参数的变化, 系统将经历边界碰撞分岔并从周期稳态向混沌态跃变, 导致系统中瞬时队列的长度出现剧烈振荡, 严重影响系统性能. 根据不动点的线性稳定条件, 提出了一种混沌控制方法,通过对系统不动点邻域内的状态变量进行扰动, 将系统引导至不动点. 该方法能显著提高TCP-RED系统的性能和资源利用率. 仿真结果证明了该方法的有效性. 关键词： 传输控制协议 随机早期检测 边界碰撞分岔 混沌控制