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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 6

Joint optimization algorithm for dynamic server deployment and task offloading in edge computing

Bai Wenchao
Lu Xianling
School of Internet of Things, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2024.11.0462

Abstract

In mobile edge computing, the fixed locations of edge server deployments can lead to imbalanced resource utilization of edge servers, resulting in increased latency and energy consumption during the task offloading process. To address this issue, this paper proposed a hierarchical reinforcement learning-based joint optimization algorithm. First, it decomposed the problem of edge server placement and task offloading and transformed them into a bi-Markov decision process. Then, it constructed a global intelligent agent model for higher-level edge server deployment using the deep Q-network, and accelerate model convergence by introducing the K-means algorithm to provide high-quality samples for the higher-layer policy. It built a lower-layer multi-agent model for task offloading using the multi-agent proximal policy optimization algorithm, and improved training stability by introducing state normalization to reduce the states feature scale differences in the lower-layer policy. Finally, it achieved the ultimate optimization goal through alternating optimization of the higher-layer and lower-layer policies. Simulation results indicate that the proposed algorithm can achieves optimal server deployment and task offloading strategies, compared to random strategies and other reinforcement learning algorithm, the proposed algorithm demonstrates greater benefits in terms of model training efficiency, target rewards, and load balancing metrics.

Foundation Support

国家自然科学基金资助项目(61773181)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.11.0462
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 6

Publish History

[2025-03-10] Accepted Paper

Cite This Article

白文超, 卢先领. 边缘计算中动态服务器部署与任务卸载联合优化算法 [J]. 计算机应用研究, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0462. (Bai Wenchao, Lu Xianling. Joint optimization algorithm for dynamic server deployment and task offloading in edge computing [J]. Application Research of Computers, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0462. )

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.

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