Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 7
2050-2055

Improved particle swarm algorithm for task offloading in vehicular networks

Miao Yuqing1
Xu Yi1
Zhang Wanzhen2
Liu Tonglai1,3
Han Zheng1
1. School of Computer & Information Security, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
2. Dept. of Practice Teaching, Guilin University of Aerospace Technology, Guilin Guangxi 541004, China
3. School of Computers, Guangdong University of Technology, Guangdong 510006, China
DOI: 10.19734/j.issn.1001-3695.2020.08.0222

Abstract

At present, most existing works focus on offloading tasks to MEC servers, in view of the total process time of the computation tasks. However, the on board unit(OBU) still has its computing capacity. To solve these problems, this research aimed to optimize the time and energy consumption of tasks and proposed a collaborative multi-task computing offloading model, where OBU in the task-solving vehicle and neighbor vehicles compute in collaboration with the MEC servers. This model also considered the energy and time consumption as well as priority among different tasks. It introduced the idea of simulated annealing and the constriction coefficient to improve the particle swarm optimization algorithm and got solution. Experimental results show that compared with other offloading strategies, the proposed task offloading strategy has obvious effects on the total cost optimization, the solutions quality of TPSO is 53.8% of PSO algorithm, 27.1% of the LOCAL-MEC strategy and 78% of the DCOS, and it can adapt to various application scenarios.

Foundation Support

国家自然科学基金资助项目(61763007,61866007)
广西自然科学基金联合资助项目(2018GXNSFAA138082)
广西密码学与信息安全重点实验室项目(GCIS201816)
广西重点研发计划资助项目(桂科AA17204002)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.08.0222
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 7
Section: Algorithm Research & Explore
Pages: 2050-2055
Serial Number: 1001-3695(2021)07-024-2050-06

Publish History

[2021-07-05] Printed Article

Cite This Article

缪裕青, 徐伊, 张万桢, 等. 车联网中改进粒子群算法的任务卸载策略 [J]. 计算机应用研究, 2021, 38 (7): 2050-2055. (Miao Yuqing, Xu Yi, Zhang Wanzhen, et al. Improved particle swarm algorithm for task offloading in vehicular networks [J]. Application Research of Computers, 2021, 38 (7): 2050-2055. )

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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