Edge Computing Resource Allocation and Optimization Method and Its Application in Internet of Vehicles Environment

Abstract

With the emergence of new vehicle-mounted services, such as autonomous driving and augmented reality, the computing capability at the edge of the Internet of vehicles (IoV) has become increasingly demanding, and the edge computing of the IoV has also emerged. With the rise of the IoV, new vehicle-mounted applications keep emerging. Vehicle-mounted applications need to process the sensor data of themselves and other vehicles around them. The amount of data is huge, and processing these sensor data requires powerful computing power. But typical vehicles have limited computing power, so such computation-intensive tasks need to be uploaded to a data center for processing. The MEC (Mobile Edge Computing) technology is a good choice to solve this problem. This paper advocates reasonable scheduling of parked vehicles to cooperate with edge servers for collaborative edge computing and studies the resource scheduling scheme under the target of user relative satisfaction. This paper describes the main entities and related functions in the network and proposes a secure and reliable protocol for interaction between entities. The serviceability of different parked vehicles in collaborative edge computing was evaluated to select stable task performers and solve the resource scheduling optimization problem between parked vehicles and edge servers. The simulation results show that the proposed scheme has better customer satisfaction and maximum overhead than the existing scheme that only considers using edge server to perform tasks. Therefore, the method of this paper has important theoretical significance and potential practical value.