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现有研究将复用的自相似业务流Hurst参数值确定为各个业务流中最大的H参数值,与业务流的其他性质无关,这一结论用于网络设备的设计不利于网络资源的有效利用。本文采用简单近似估算,并用分形布朗运动模型生成自相似业务流,采用小波分析方法估计Hurst 参数值。实验结果表明,由于复用合成业务流的渐近自相似的本质,在可以观测的时间尺度范围内业务流的Hurst参数比这理论预测值小;在一定的序列长度下,复用流的Hurst参数的不仅和最大Hurst参数业务流有关,还受到其它业务流,特别是业务流的方差系数所表现出的短时突发性影响,因此对合成业务流的自相似参数具有重要的影响。
In the existing research, the value of the Hurst parameter of the self-similar service stream multiplexed is determined as the largest H parameter value in each service stream, which has nothing to do with other properties of the service stream. This conclusion is used to design the network device is not conducive to the efficient use of network resources . In this paper, a simple approximate estimation is used, and a self-similar traffic flow is generated by a fractal Brownian motion model. The Hurst parameters are estimated by wavelet analysis. The experimental results show that the Hurst parameter of the service flow is smaller than the theoretical prediction value due to the asymptotic self-similar nature of the multiplexed composite service flow over the observable time scale. Under a certain sequence length, the Hurst The parameters are not only related to the maximum Hurst parameter traffic but also have a short-term and sudden impact on the variance coefficients of other traffic flows, especially the traffic flows. Therefore, the parameters have a significant impact on the self-similar parameters of the composite traffic flows.