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CLC number: TP393

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2015-08-06

Cited: 1

Clicked: 6733

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jie Shen

http://orcid.org/0000-0003-4391-813X

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

http://doi.org/10.1631/FITEE.1400414


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",
doi="10.1631/FITEE.1400414"
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Abstract: 
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.

网络系统的端到端延时分析

目的:面向大规模复杂网络,提出一种有效的端到端延时的分析方法,保障网络服务性能。
创新点:基于频域分析方法提出一种新的网络延时分析方法,具有高效率的特点。
方法:首先,将网络系统的延时从时域转换到频域,并用信号流图建模(图1)。然后,用克莱姆法则或者梅森增益公式计算信号流图模型的传递函数。接着,分析传递函数的脉冲响应和阶跃响应得到系统的端到端延时的概率密度函数和概率分布函数(图2)。最后,用该方法分析两个实际例子。包括:第一,用该方法得到网络中的瓶颈链路(图3、4);第二,用该方法分析网络通信协议(图6)。
结论:针对大规模复杂网络,提出基于频域分析的网络延时分析方法,这种方法是有效的。

关键词:网络系统;端到端;延时分布

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

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