Joint Computing and Caching in 5G-Envisioned Internet of Vehicles: A Deep Reinforcement Learning-Based Traffic Control System

• Published in: IEEE transactions on intelligent transportation systems Vol. 22; no. 8; pp. 5201 - 5212
• Main Authors: Ning, Zhaolong, Zhang, Kaiyuan, Wang, Xiaojie, Obaidat, Mohammad S., Guo, Lei, Hu, Xiping, Hu, Bin, Guo, Yi, Sadoun, Balqies, Kwok, Ricky Y. K.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial intelligence; Caching; content caching; Control systems; Deep learning; deep reinforcement learning; Edge computing; Intelligent transportation systems; Internet of connected vehicles; Internet of Vehicles; Machine learning; Optimization; Quality of experience; Resource management; Servers; Task analysis; Traffic control; traffic control system; Traffic information; Transportation networks; User experience; Vehicles; Wireless networks

Recent developments of edge computing and content caching in wireless networks enable the Intelligent Transportation System (ITS) to provide high-quality services for vehicles. However, a variety of vehicular applications and time-varying network status make it challenging for ITS to allocate resour...