Data burst statistics and performance analysis of optical burst switching networks with self-similar traffic

被引：0
|
作者：
Wang Ruyan [1 ]
Wu Dapeng [2 ]
Guo Fang [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing 400065, Peoples R China
[2] Beijing Univ Posts & Telecommun, Broadband Commun Network Lab, Beijing, 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
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/SNPD.2007.450
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The self-similar model can reflect the Internet traffic property more precisely than Poisson model, the theoretical and simulation results of burst length distribution based on the time threshold assembly mechanism are shown in this paper. Moreover, the simulation result of OBS schedule algorithm under self-similar traffic model is reported Both the analytic and simulation results show that burst length distribution is related to the length of assembly period; secondly, the assembly mechanism based on time period can reduce the self-similarity of traffic effectively; at last, the schedule algorithms in OBS have different performance based on the self-similar traffic.
引用
收藏
页码：974 / +
页数：2
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