Study on Self-adaptive Systematic Double Sampling method for Self-similar Network Traffic

被引：0
|
作者：
Liu Yuanzhen Liu Yuan Li Xiaohang School of Information Engineering
机构：
来源：
China Communications | 2007年 / 4卷 / 02期
关键词：
self-similarity; Hurst parameter; double sampling;
D O I：
暂无
中图分类号：
TP393.06 [];
学科分类号：
081201 ; 1201 ;
摘要：
This paper proposes anew variation of systematic sampling, called Self-Adaptive Systematic Double Sampling(SSDS). This algorithm can fully consider the self-similar and heavy-tailed distribution characteristics of network traffic and estimate Hurst parameter correctly.The experiments on real Internet traces indicate,compared with traditional sampling methods,the new method advances the accuracy and practicability of the sampling measuring system obviously,and can achieve simplicity,adaptability and controllability of resource consumption.
引用
收藏
页码：86 / 89
页数：4
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