Computation task offloading algorithm and system level simulation for vehicles - Qicheng ZENG; Yuxuan SUN; Sheng ZHOU (物联网学报)
With the development of autonomous driving and vehicular network,more and more vehicles will have powerful computing capabilities and connection with each other via wireless network.These computing resources can not only be applied to automatic driving,but also provide a wide range of edge computing services.Aiming at the task offloading among vehicles,a distributed task offloading algorithm based on online learning was proposed to minimize the average offloading delay.Furthermore,a system-level simulation platform was built to evaluate the impact of vehicle density and number of tasks on the average offloading delay in both highway and urban scenarios.The results provide a reference for the resource allocation and deployment of task offloading in different traffic situations.