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Article type: Research Article
Authors: Ren, Jianjia | Yang, Donghaoa | Yuan, Yongliangb; * | Liu, Haiqingc | Hao, Binc | Zhang, Longliec
Affiliations: [a] School of Software, Henan Polytechnic University, Jiaozuo, Henan, China | [b] School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo, Henan, China | [c] Do-fluoride New Energy Technology Co, Ltd, Jiaozuo, China
Correspondence: [*] Corresponding author. Yongliang Yuan, School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan, China. Email: yuanyongliang@hpu.edu.cn.
Abstract: The utilization of green edge has emerged as a promising paradigm for the development of new energy vehicle (NEV). Nevertheless, the recharging of these vehicles poses a significant challenge in due to limited power resources and enormous transmission demands. A novel architecture based on Wifi-6 communication is proposed, which makes the most of heterogeneous edge nodes to achieve real-time processing and computation of tasks. To address the collaborative power resource optimization problem, the interference between different vehicles is considered, and the task offloading is optimized. In particular, the power contention among recharging clusters is modeled as an exact game and a task offloading strategy model is proposed jointly with the Deep Q-Network (DQN) algorithm, which is employed by a secondary application. Thereby, the recharging efficiency and task offloading computation are optimized and improved. Results indicate that the total resource consumption is favorably improved with this architecture and algorithm and the Nash equilibrium is also demonstrated.
Keywords: Energy management, vehicle recharging, heterogeneous node gaming, computation offloading, recharging efficiency
DOI: 10.3233/JIFS-233990
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 479-492, 2024
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