自相似流量关键参数分析

大量的研究结果表明,网络流量过程普遍存在着自相似和长相关特性,自相似和长相关特性对网络性能具有重要的影响.目前绝大部分研究都集中在Hurst系数的估计及其性能影响上,这是不全面的.本文深入研究影响网络性能的自相似流量关键参数,通过仿真分析Hurst系数和方差系数对网络性能的影响,表明Hurst系数和方差系数对网络性能均有重要的影响.分析了方差对网络性能影响的原因,研究了G与方差之间的关系及其计算方法,给出了基于IDC的复合分形更新过程参数的估计算法,分析了分形开始时间对网络性能的影响.

Analysis of Key Parameters of Self-similar Traffic

There is mounting experimental evidence that network traffic processes exhibit ubiquitous properties of self-similarity and long-range dependence (LRD),and self-similarity and long-range dependence have great impact on network performances. However,most current researches on self-similar traffic mainly focus on the estimation of Hurst index and its impact on network performances,which is not overall. In this paper,the key parameters impacting the network performances of self-similar traffic are investigated...