In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 3

Co-computation offloading method based on boosting prioritized empirical replay

Huang Yia,b,c,d
Wang Wenxuana,b,c,d
Cui Yunhea,b,c,d
Chen Yia,b,c,d
Guo Chuna,b,c,d
Shen Guoweia,b,c,d
a. State Key Laboratory of Public Big Data, b. Engineering Research Center of Text Computing & Cognitive Intelligence, Ministry of Education, c. College of Computer Science & Technology, d. Key Laboratory of Software Engineering & Information Security in Guizhou Province, Guizhou University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2024.08.0313

Abstract

The existing computation offloading methods have not considered different task queues in terminal devices and edge servers, resulting in queuing latency estimating error of computation offloading model. More important, the existing computation offloading methods based on reinforcement learning perform experience replay by calculating Temporal Difference (TD) error, which cannot accurately assess the importance of historical experience, resulting in lower offloading decision accuracy. To address the above issues, in the mobile cellular network edge computing scenario, this paper considered the problem of computation offloading with multiple devices and servers, and proposed a cooperative computation offloading method based on Boosting prioritized experience replay-COOPERANT. For the task scheduling problem, COOPERANT constructed terminal device task queuing models and server task queuing models. For the task offloading problem, COOPERANT designed a prioritized experience replay algorithm that integrates Boosting, a joint optimization model for task offloading, a multi-agent deep reinforcement learning model for computation offloading, and a COOPERANT network updating mechanism. Experimental results have shown that COOPERANT can effectively reduce system latency and energy consumption and improve the network convergence speed compared to genetic algorithm, ant colony algorithm, whale optimization algorithm, MADDPG algorithm, TD-MADDPG algorithm, and the MAPPO algorithm.

Foundation Support

国家重点研发计划(2023YFC3304500)
国家自然科学基金资助项目(62102111)
贵州省科技重大专项(黔科合重大专项字[2024]003)
贵州省高等学校大数据安全与网络安全创新团队(黔教技[2023]052号)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.08.0313
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 3

Publish History

[2024-12-16] Accepted Paper

Cite This Article

黄毅, 王文轩, 崔允贺, 等. 基于Boosting优先经验重放的协同计算卸载方法 [J]. 计算机应用研究, 2025, 42 (3). (2024-12-16). https://doi.org/10.19734/j.issn.1001-3695.2024.08.0313. (Huang Yi, Wang Wenxuan, Cui Yunhe, et al. Co-computation offloading method based on boosting prioritized empirical replay [J]. Application Research of Computers, 2025, 42 (3). (2024-12-16). https://doi.org/10.19734/j.issn.1001-3695.2024.08.0313. )

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)