基于相空间重构的计算机网络的动力学特性分析

Analysis on Computer Network's Dynamics Based on Reconstruction of Phase Space

文章利用相空间重构理论对网络流量数据进行研究分析,用单变量的网络流量时间序列重构与网络动力系统等距同构的相空间,进而计算网络的关联维数、Kolmogorov熵和最大Lyapunov指数,研究网络系统的这三个参数随时间的变化特性。从而指出了网络流量具有的混沌动力学行为,并为进一步利用混沌动力学理论对网络行为的控制和建模奠定了基础。

A new method based on reconstruction theory of the phase space is presented to analyze network flow data.The Fractal dimension,Kolmogorov entropy and the largest Lyapunov exponents of the reconstructed phase-space are calculated from the one dimensional time sequence of network flow.The study on the temporal characteristics of these three parameters,discovered that the network flow is featured by some chaotic behaviors,and thus can be effectively ex-ploited for the controlling and modeling of the network behaviors.