基于强化学习的边缘计算智能电网资源调度算法

Edge computing smart grid resource scheduling algorithm based on reinforcement learning

智能电网是一种能够进行智能管理和优化的电力网络。网络虚拟化技术可以有效提高智能电网的资源利用率和可靠性,从而满足不同用户的差异化需求。在资源有限的情况下,传统的虚拟网络嵌入算法无法根据电力系统的资源使用情况和用户需求来动态调整虚拟资源的分配和映射。为解决这一问题,将边缘计算和虚拟化技术相结合,引入了一种基于强化学习的虚拟网络资源调度算法。仿真结果表明,该虚拟网络资源调度算法在提高电网的可靠性和资源利用率方面优于其他3种调度算法。

A smart grid is a power network capable of intelligent management and optimization.Network virtualiza-tion technology can effectively improve the resource utilization and reliability of smart grids and meet the differenti-ated needs of different users.In the case of limited resources,traditional virtual network embedding algorithms can-not dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem,edge computing and virtualization technology was combined and a virtu-al network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization.