Green Internet of Vehicles: Architecture, Enabling Technologies, and Applications

• Main Authors: Handi Chen, Tingting Zhao, Chengming Li, Yi Guo
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Green Internet of Vehicles; 5G; mobile edge computing; deep reinforcement learning
• Online Access: https://ieeexplore.ieee.org/document/8926352/

With the development of Internet of Vehicles (IoV) and the gradual maturity of 5th Generation Mobile Networks (5G) technology, the further development of the IoV highly relies on network energy and resources. However, basic methods of researching new energy or improving equipment result in high cost. This article focuses on researching how to minimize energy consumption and maximize resource utilization with the constraints of existing environment and equipment. We jointly discuss 5G technology, mobile edge computing and deep reinforcement learning in green IoV. We also discuss how to make rational use of resources to realize the sustainable development of IoV. By classifying and comparing the existing researches according to different emphases, the energy consumption can be managed effectively with the above-mentioned technologies. Finally, we analyze the possible research directions and challenges in the future.