Abstract: With the deployment of the Internet of vehicles and the constant emergence of intelligent vehicular applications, the computing power of vehicular terminals is no longer sufficient to meet the demand of intelligent vehicular applications. A large number of vehicular computing tasks are offloaded to the edge computing network. It has become a challenge for research on the vehicle edge computing network to ensure fast and reasonable allocation of computing tasks, reduce latency, and improve user service quality. This paper focuses on the resource allocation problem of vehicular task offloading and comprehensively considers factors, such as the local computing latency of vehicular tasks, the computing latency of vehicular tasks in edge servers and network latency, and the network latency generated by the migration of vehicular tasks in edge clouds. In this paper, we propose an optimal control-based load balancing strategy for vehicular edge computing first network. The strategy solves the load balancing, resource allocation, and task migration by considering the load status of the edge server and the disturbance of the computing load. Simulation experiments show that regardless of whether there is disturbance or not, the load balancing effect of the strategy proposed in this paper is better than the state-of-the-art methods.

Key words: vehicular edge computing first network, task migration, load balance, optimal control