Technology of Network & Communication
|
App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 11
3456-3460,3466

SFC mapping algorithm based on deep reinforcement learning

Jin Ming1
Li Linlin1
Zhang Wenjin2
Liu Wen3
1. School of Operational Support, Rocket Force University of Engineer, Xi'an 710000, China
2. 96941 Troops of PLA, Beijing 100089, China
3. 96872 Troops of PLA, Baoji Shaanxi 721000, China
DOI: 10.19734/j.issn.1001-3695.2019.08.0278

Abstract

This paper proposed an algorithm for SFC mapping based on deep reinforcement learning which was called DQN-SFC, aiming at reducing the influence of SFC mapping on the average time delay and deployment failure ratio in the network. Firstly, it constructed a multi-layer NFV management and scheduling architecture to meet the requirements of resource awareness and equipment configuration of the algorithm. Secondly, based on Markov decision process, it formally described the SFC mapping problem. Finally, it constructed a deep reinforcement learning network, which used the average network delay and the operation expense of the deployment as reward and punishment feedback. After training, the target position of the virtual network function where to be deployed can be determined according to the network status. The simulation experiment verifies correctness and performance of this algorithm. Experiment shows that this algorithm can effectively reduce the average network delay and deployment failure ratio, and has certain advantages in algorithm running time.

Foundation Support

国家自然科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.08.0278
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 11
Section: Technology of Network & Communication
Pages: 3456-3460,3466
Serial Number: 1001-3695(2020)11-052-3456-05

Publish History

[2020-11-05] Printed Article

Cite This Article

金明, 李琳琳, 张文瑾, 等. 基于深度强化学习的服务功能链映射算法 [J]. 计算机应用研究, 2020, 37 (11): 3456-3460,3466. (Jin Ming, Li Linlin, Zhang Wenjin, et al. SFC mapping algorithm based on deep reinforcement learning [J]. Application Research of Computers, 2020, 37 (11): 3456-3460,3466. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)