Real-Time Scheduling Strategy for Cloud-Edge-End Collaborative Electric Vehicles Considering Energy Consumption
Xudong Song, Xiaomin Sun, Zhiyong Li, Cuiru Yang, Ya Wu · 2023
In this paper, a small server with local processing capability is added to the terminal on the basis of energy consumption. As described in the server energy consumption report and the base station communication energy consumption report, a cloud-edge collaboration task offloading strategy considering energy consumption is proposed to reasonably offload the tasks of electric vehicles (EVs) participating in scheduling, and by using particle swarm algorithms, time delay and energy consumption are used as optimization obj ectives. The simulation results show that the cloud-edge collaboration unloading strategy considering energy consumption further improves the grid response efficiency in the scheduling process, and the proposed strategy provides a reference for the future real-time demand response scheduling of a large number of EV s.