Mobile Edge Computing and Resource Scheduling of Internet of Vehicles

Recent advances in edge computing had significant impacts on the development of internet of vehicles. However, the internet of vehicles are confronted with serious challenge in terms of deployment unbalanced, computing resource allocation unbalanced and time delay on real-time computing because of the roadside edge computing nodes. In this paper, a task queuing model and computing resource dynamic scheduling policy are proposed. Firstly, a mobile edge computing (MEC) architecture is designed to build elastic distributed services in vehicular networks environment. Then, the M/M/1 task queueing model is constructed by queue theory and tasks generated by virtual vehicles are assigned and changed access to the MEC server according to cell switch model. Moreover, the additive increase multiplicative decrease (AIMD) algorithm are presented to solve the imbalance of computing resource allocation. The simulation results illustrate the effectiveness of the proposed method.