自相似网络流量Hurst指数估计算法

摘要

Since Hurst index is the key value of self-similar network traffic,efficient estimation of Hurst index to the given accuracy is the basic step of flow control as well as buffer management in high-speed broadband network (e.g.ATM) with self-similar traffic.A Hurst index estimation method based on DFGN model and Haar wavelet is proposed.Simulation results based on DFBM and real traffic data reveal that the method improves accuracy and efficiency compared to the traditional method.%Hurst参数是表征网络业务自相似性的重要参数,在一定的观察时间内对突发业务的Hurst参数进行快速、准确地估计是高速宽带网络(如ATM)实施流量控制和缓冲资源分配的前提.提出一种基于DFGN模型和Haar小波的Hurst参数估计方法.仿真生成的DFBM和真实自相似网络业务数据的计算结果均表明,所述方法提高了Hurst参数估计的效率和准确性,比传统方法具有更好的性能.