App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

Energy optimization framework for fast deployment and task offloading in multi-uav collaboration

Jing Chao1a,1b
Wu Shouyi1a,2
Qin Fengping1c
1. a. School of Computer Science and Engineering, b. Guangxi Key Laboratory of Embedded Technology and Intelligent System, c. Guilin university of Technology at Nanning college of computer applications, Guilin University of Technology, Guilin Guangxi 541004, China
2. Guangxi Academy of Artificial Intelligence, Nanning 530200, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0045

Abstract

In the context of multi-UAV-assisted edge computing, this paper investigates rapid UAV deployment and energy consumption optimization during task offloading and proposes a cooperative energy optimization framework (Co-EOF) for multiple UAVs. Under latency constraints, the framework optimizes energy consumption by jointly optimizing UAV deployment and intelligent offloading decisions. Co-EOF consists of two layers: the UAV response deployment layer and the task offloading decision layer. To obtain the optimal initial deployment of UAVs, the deployment layer employs a rapid UAV deployment strategy based on an improved particle swarm optimization algorithm. Based on the optimal deployment locations, the task offloading decision layer further integrates an improved twin delayed deep deterministic policy gradient deep reinforcement learning algorithm (SOPM3) to perform task offloading and resource allocation, thereby minimizing energy consumption while satisfying latency requirements. Finally, this paper develops a simulation platform for multi-UAV-assisted edge computing and conducts extensive experiments. Compared with various benchmark algorithms, the experimental results show that Co-EOF achieves lower energy consumption under different latency constraints, task data sizes, and user counts than the best-performing benchmark algorithms, while also attaining higher task completion rates.

Foundation Support

广西重点研发项目(桂科AB23026034,桂科AB23075116)
广西人工智能学院研究生创新项目(RD2500003512)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0045
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-07-29] Accepted Paper

Cite This Article

敬超, 吴守毅, 覃凤萍. 面向多无人机协同的快速部署及任务卸载能耗优化框架 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0045. (Jing Chao, Wu Shouyi, Qin Fengping. Energy optimization framework for fast deployment and task offloading in multi-uav collaboration [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0045. )

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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