A Resource Scheduling Method for Mobile Cloud Computing based on Maximum Revenue
Jianhui Li, Manlan Liu, Jianxi Peng, Xinyue Feng, Wuping Liu · 2023
With the rapid development of automatic driving technology, the demand for downloading large files online has experienced explosive growth. Due to the local computing capacity, resource scheduling algorithms for large-scale file requests often have higher response delay and lower scheduling efficiency. In this paper, a priority based maximum revenue vehicle cloud computing resource scheduling algorithm is proposed. This algorithm uses an improved dynamic greedy algorithm to establish the system revenue model of the device in the scene. The algorithm considers the priority of vehicle requests, the amount of request data, and the user allowed time and other factors to maximize the revenue. The simulation results show that the algorithm can obtain the optimal resource allocation of vehicle collaboration by changing different parameter settings, and has good practicability and feasibility.