Affiliation:
1. School of Electronic and Information Engineering Beijing Jiaotong University Beijing China
Abstract
AbstractHigh‐dependability Internet of Vehicle (IoV) is essential for urban transit, since it contributes to the safe operation of vehicles, and even to the safety of the entire city. This paper introduces the IoV cluster model with network slicing. Based on this model, an integrated vehicles clustering and network slicing scheme for IoV networks is introduced to guarantee the dependability of different traffics in IoV. The network slicing scheme is proposed to divide the wireless frequency resource of the IoV network into separate logical networks. A analysis model, based on age of information, is utilized as an integrated indicator for evaluating the dependability of the IoV system in urban transit. Asynchronous reinforcement learning with advantage actor‐critic is employed to optimize the integrated dependability of IoV. It is demonstrated in simulations that the proposed IoV cluster incorporating the network slicing scheme can guarantee the integrated dependability of the IoV system. Moreover, by the application of reinforcement learning, the system dependability can be further improved.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Institution of Engineering and Technology (IET)
Subject
Law,Mechanical Engineering,General Environmental Science,Transportation
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献