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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2738-2744

DQN-based driverless task offloading policy

Wang Jin
Zhang Xinyou
School of Computing & Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China
DOI: 10.19734/j.issn.1001-3695.2022.02.0043

Abstract

Due to its limited battery life and computing power, driverless cars are difficult to meet the processing needs of some delay-sensitive tasks or intensive tasks while ensuring battery life. To solve this problem, in the context of MEC, this paper proposed a driverless task offloading policy based on deep DQN. Firstly, this paper defined a "vehicle-edge-cloud" cooperative task offloading model based on task priority, which needed to jointly optimize the computing power of the vehicle and the task offloading policy to obtain the minimum delay and energy consumption of the system. Since the problem was a mixed-integer nonlinear programming problem and was NP-hard, this paper solved it in two steps—the first step obtained the analytical solution for the optimal computation power of vehicle through mathematical derivation, and then, under the fixed numerical value condition, the DQN algorithm obtained the optimal offloading strategy of the task. Finally, this paper established a simulation model by integrating tools such as SUMO, PyTorch and Python. This paper compared the DQN algorithm and the other three algorithms under different task loads, MEC server computation powers and energy consumption weight co-efficients. The experimental results verify the feasibility and superiority of the proposed policy.

Foundation Support

国家自然科学基金资助项目(61802319)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.02.0043
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Algorithm Research & Explore
Pages: 2738-2744
Serial Number: 1001-3695(2022)09-027-2738-07

Publish History

[2022-04-15] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

王锦, 张新有. 基于DQN的无人驾驶任务卸载策略 [J]. 计算机应用研究, 2022, 39 (9): 2738-2744. (Wang Jin, Zhang Xinyou. DQN-based driverless task offloading policy [J]. Application Research of Computers, 2022, 39 (9): 2738-2744. )

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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