Full Text:   <2473>

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CLC number: TP393

On-line Access: 2015-09-06

Received: 2014-12-04

Revision Accepted: 2015-07-18

Crosschecked: 2015-08-06

Cited: 1

Clicked: 5962

Citations:  Bibtex RefMan EndNote GB/T7714


Jie Shen


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Frontiers of Information Technology & Electronic Engineering  2015 Vol.16 No.9 P.732-743


End-to-end delay analysis for networked systems

Author(s):  Jie Shen, Wen-bo He, Xue Liu, Zhi-bo Wang, Zhi Wang, Jian-guo Yao

Affiliation(s):  Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   jshen@iipc.zju.edu.cn, wangzhi@iipc.zju.edu.cn

Key Words:  Networked system, End-to-end, Delay distribution

Jie Shen, Wen-bo He, Xue Liu, Zhi-bo Wang, Zhi Wang, Jian-guo Yao. End-to-end delay analysis for networked systems[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(9): 732-743.

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publisher="Zhejiang University Press & Springer",

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T1 - End-to-end delay analysis for networked systems
A1 - Jie Shen
A1 - Wen-bo He
A1 - Xue Liu
A1 - Zhi-bo Wang
A1 - Zhi Wang
A1 - Jian-guo Yao
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 16
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1400414

end-to-end delay measurement has been an essential element in the deployment of real-time services in networked systems. Traditional methods of delay measurement based on time domain analysis, however, are not efficient as the network scale and the complexity increase. We propose a novel theoretical framework to analyze the end-to-end delay distributions of networked systems from the frequency domain. We use a signal flow graph to model the delay distribution of a networked system and prove that the end-to-end delay distribution is indeed the inverse Laplace transform of the transfer function of the signal flow graph. Two efficient methods, Cramer’s rule-based method and the Mason gain rule-based method, are adopted to obtain the transfer function. By analyzing the time responses of the transfer function, we obtain the end-to-end delay distribution. Based on our framework, we propose an efficient method using the dominant poles of the transfer function to work out the bottleneck links of the network. Moreover, we use the framework to study the network protocol performance. Theoretical analysis and extensive evaluations show the effectiveness of the proposed approach.

In this paper, the authors proposed a novel theoretical framework to analyzed end-to-end delay distributions. This paper deals with the very interesting and important issue on large-scale networked systems. By analyzing the end-to-end delay, large-scale networked systems can be improved by improving the delay distribution of bottleneck link. Overall, this paper is well organized and well written.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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