Statistical modeling and correlation analysis of end-to-end delay in wide area networks

被引：6

作者：

Zhang, Wei ^{[1
]}

He, Jingsha ^{[2
]}

机构：

[1] Beijing Univ Technol, Coll Comp Sci & Technol, Beijing 100022, Peoples R China

[2] Beijing Univ Technol, Sch Software Engn, Beijing 100022, Peoples R China

来源：

SNPD 2007: EIGHTH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING, AND PARALLEL/DISTRIBUTED COMPUTING, VOL 3, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/SNPD.2007.490

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

End-to-end delay is a very important network performance parameter. Consequently, research on end-to-end delay has received a great deal of interest. In this paper, we model end-to-end delay using statistical methods. In particular, we use three statistical distribution models to study end-to-end delay, i.e., Pareto distribution, normal distribution and lognormal distribution. Our analysis results show that Pareto distribution is most appropriate to model end-to-end delay while normal or normal-related distribution is not. We also study delay correlation in different time ranges to find out if delay in the past can provide any indication on delay in the future. Our study shows that there is indeed a good correlation when the time range is about 1.25 seconds.

引用

页码：968 / +

页数：2