Investigation on the IP Flow Inter-arrival Time in Large-scale Network
被引:6
作者:
Wu, Hua
论文数: 0引用数: 0
h-index: 0
机构:
Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R ChinaSoutheast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China
Wu, Hua
[1
]
Zhou, Mingzhong
论文数: 0引用数: 0
h-index: 0
机构:
Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R ChinaSoutheast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China
Zhou, Mingzhong
[1
]
Gong, Jian
论文数: 0引用数: 0
h-index: 0
机构:
Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R ChinaSoutheast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China
Gong, Jian
[1
]
机构:
[1] Southeast Univ, Sch Comp Sci & Engn, Nanjing, Peoples R China
来源:
2007 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-15
|
2007年
关键词:
large-scale networks;
IP flows;
inter-arrival time distribution model;
flow length;
autocorrelation;
D O I:
10.1109/WICOM.2007.482
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
This paper analyzes the IP now inter-arrival time distribution and the inter-arrival time autocorrelations of the traces collected in different large-scale networks. It is found that the IP flow inter-arrival time distribution follows the Weibull distribution which has the parameter alpha close to 1.0 as the scale of network becomes larger, so the Weibull distribution degrades to the Exponential distribution. It is also discovered that the autocorrelation decreases as the IP flows' length increases. According to the studies above, this paper deduces the conclusion as following: The IP flow inter-arrival time distribution fits to the Weibull distribution generally, when the IP flow length exceed a certain threshold, the W flow interarrival time fits to the Poisson distribution.