Technology of Network & Communication
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 12
3749-3752,3776

Construction strategy of data stream mutation service function chain based on machine learning

Zhao Jihong1,2
Ji Wenjun1
Qu Hua2
Zhao Jianlong2
Wang Ke2
Wu Doudou1
1. School of Communications & Information Engineering, Xi'an University of Posts & Telecommunications, Xi'an 710121, China
2. School of Electronic & Information Engineering, Xi'an Jiaotong University, Xi'an 710054, China
DOI: 10.19734/j.issn.1001-3695.2019.07.0548

Abstract

In the enhanced mobile broadband scenario under SDN/NFV network architecture, this paper studied the problem of low availability of service function chain due to data stream mutation, and proposed a dynamic service function chain construction strategy based on heuristic closed-loop feedback algorithm. The algorithm had two parts, such as service function chain deployment module and feedback adjustment module. Firstly, it implemented the initial deployment of the service function chain based on the resource optimization model and used the genetic algorithm to solve the optimization model. Then, it used the random forest regression algorithm to predict the data traffic that could be carried by the current service function chain to achieve the corresponding feedback adjustment. Therefore, the whole service function chain construction strategy was a heuristic closed-loop feedback algorithm based on genetic algorithm and random forest regression. The simulation results show that compared with the existing genetic and tabu search algorithms, the proposed algorithm improves the user acceptance rate by 12% and the occupancy of the underlying resources by 19%.

Foundation Support

国家自然科学基金资助项目(61531013)
国家重大专项资助项目(2018ZX03001016)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.07.0548
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 12
Section: Technology of Network & Communication
Pages: 3749-3752,3776
Serial Number: 1001-3695(2020)12-046-3749-04

Publish History

[2020-12-05] Printed Article

Cite This Article

赵季红, 季文君, 曲桦, 等. 基于机器学习数据流突变型服务功能链构建策略 [J]. 计算机应用研究, 2020, 37 (12): 3749-3752,3776. (Zhao Jihong, Ji Wenjun, Qu Hua, et al. Construction strategy of data stream mutation service function chain based on machine learning [J]. Application Research of Computers, 2020, 37 (12): 3749-3752,3776. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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