Research on heterogeneous radio access and resource allocation algorithm in vehicular fog computing - Kai XIONG; Supeng LENG; Ke ZHANG; Hao LIU (物联网学报)
With the development of intelligent transportation and the constant emergence of new vehicular on-board applications,such as automatic driving,intelligent vehicular interaction and safety driving.It is difficult for an independent vehicle to run a wide variety of applications with a large number of computing needs and time delay needs relying on its own limited computing resources.By distributing computing tasks in devices on the edge of the network,fog computing applies virtualization technology,distributed computing technology and parallel computing technology to enable users to dynamically obtain computing power,storage space and other services on demand.Applying fog computing architecture to Internet of vehicles can effectively alleviate the contradiction between the large computing-low delay demands and limited vehicular resources.By analyzing the channel capacity of vehicle-to-vehicle communication,vehicle-infrastructure communication and vehicle-time-delay tolerant network communication,an optimization model of heterogeneous access to multi-service resources for the Internet of vehicles was established,and various vehicle-to-fog resources were jointly dispatched to realize efficient processing of intelligent transportation applications.The simulation results show that the proposed reinforcement learning algorithm can effectively deal with the resource allocation in the heterogeneous vehicular fog architecture.