Tasks-Oriented Joint Resource Allocation Scheme for the Internet of Vehicles with Sensing,Communication and Computing Integration

With the development of artificial intel-ligence(AI)and 5G technology,the integration of sensing,communication and computing in the Inter-net of Vehicles(IoV)is becoming a trend.However,the large amount of data transmission and the comput-ing requirements of intelligent tasks lead to the com-plex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the sce-nario of IoV.First,this paper proposes a system model with sensing,communication,and computing integra-tion for multiple intelligent tasks with different re-quirements in the IoV.Secondly,joint resource allo-cation problems for real-time tasks and delay-tolerant tasks in the IoV are constructed respectively,includ-ing communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization prob-lems,and the convergence and complexity of the al-gorithm are discussed.Finally,the experimental re-sults based on real data sets verify the performance ad-vantages of the proposed resource allocation scheme,compared to the existing ones.The exploration ef-ficiency of our proposed DDQN-based algorithm is improved by at least about 5％,and our proposed re-source allocation scheme improves the mAP perfor-mance by about 0.15 under resource constraints.