[en] The increasing complexity of modern automotive applications presents difficulties when running them on the on-board units (OBUs) of vehicles. While 5G/6G vehicular edge computing networks (VECNs) offer potential solutions through computation task offloading, ensuring prompt, energy-efficient access to these networks remains a significant challenge. To overcome these challenges, reconfigurable intelligent surfaces (RIS) can play an important role in 6G vehicular networks. With RIS, networks can provide better connectivity, increased data rate and energy efficient access, and communication channel security. In this paper, we utilize zero-energy RIS (ze-RIS) to aid vehicular computation offloading while maximizing the energy and time savings while meeting the task and environmental constraints. A joint power and offloading mechanism controlling DRL-driven RIS-assisted energy efficient task offloading (DREEO) scheme is proposed. DREEO utilizes a hybrid approach that combines binary and partial offloading mechanisms, complemented by an intelligent communication link switching mechanism. This strategy helps in saving both energy and time effectively. An efficiency factor, serving as both a performance indicator and a reward function, is introduced for the DRL agent, considering both saved energy and time. Through extensive evaluations, DREEO scheme shown an increase in task success rate from 2.13% to 7.36% and has improved the efficiency factor from 21.97 to 51.27. Furthermore, compared to other evaluated schemes, the DREEO scheme consistently outperforms them in terms of reward and the TFPS ratio, the DRL properties.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Mirza, Muhammad Ayzed ; BUPT-QMUL EM Theory and Application International Research Lab, Beijing University of Posts and Telecommunications, Beijing, China ; School of Computer and Information Science and also with Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan City, China ; Department of Computer Science, Superior University, Lahore, Pakistan
Yu, Junsheng; BUPT-QMUL EM Theory and Application International Research Lab, Beijing University of Posts and Telecommunications, Beijing, China ; School of Physics and Electronic Information, Anhui Normal University, Wuhu, China ; School of Intelligence and Digital Engineering, Luoyang Vocational College of Science and Technology, Luoyang, China
Ahmed, Manzoor ; School of Computer and Information Science and also with Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan City, China
Raza, Salman ; Department of Computer Science, National Textile University, Faisalabad, Pakistan
KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Xu, Fang ; School of Computer and Information Science and also with Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan City, China
Nauman, Ali ; Department of Information and Communication Engineering, Yeungnam University, South Korea
This research was supported by the MOE (Ministry of Education of China) Project of Humanities and Social Sciences ( 23YJAZH169 ), the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation ( T2020017 ).
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