基于小波技术的网络流量分析与刻画

Analysis and depiction of network traffic based on wavelet technique

大量研究结果表明实际网络流量具有明显的尺度特性,在大尺度上表现出自相似,在小尺度上表现出多重分形。多重分形为刻画流量在小尺度上的奇异性提供了良好的数学框架,而小波变换对具有长程依赖性的流量起到了去相关的作用,因此有必要利用小波技术来研究多重分形。为了能全面有效地刻画现代网络特征,利用小波技术对实际流量进行分析,首先判断流量的全局特性与局部特性,然后对流量进行不同分组,分别采取组内打乱和组间打乱顺序的方法,深入探讨影响多重分形的因素,最后发现均值和方差对多重分形有较大影响。

Many research studies have proposed scaling of real network traffic has a notable effect on the network performance： the self-similar phenomena over large scale, the multi-fractal phenomena over small scale. As multi-fractal providing the upstanding frame of mathematics to depict the singularity of traffic over small scale, and the wavelet transform taking effect on un-correlation to the traffic which is long range dependent, it is necessary to research the muhi-fractal model based on wavelet technique. The multi-scale provides the new method to study the characteristics of traffic. In order to depict the characteristics of modem network, the real traffic based on the wavelet technique was analyzed, and the global characteristics and local characteristics of traffic were judged at first. Then, the traffic was divided into blocks, and the traffic between inner block and outer block was mixed. At last, when studying the factors which have impact of the multi-fractal on the traffic, it is found that, the mean and variance have impact of multi-fractal on the traffic.