Abstract:Deploying edge computing nodes on the demand side can effectively reduce the pressure of data transmission and storage of the power network and improve the quality of electric power service. At present,the deployment location of edge nodes is mostly determined from the dimension of grid topology,and the service scope of nodes is defined by the grid method. The working process among nodes is independent. Therefore,the flexibility of the location and capacitydetermination of edge nodes is low, and it may cause waste of equipment computing resources.Therefore,an edge computing node deployment method considering task migration is proposed in this paper. Firstly,an edge computing architecture considering task migration is proposed based on the characteristics of edge devices and the spatial characteristics of residential areas. Secondly,feature data is formed according to spatial information and load characteristics of residential nodes. Then the number,address and service scope of nodes are determined by using the improved density peak analysis algorithm. Finally,a heuristic algorithm is designed to realize the task migration among the edge nodes to ensure the balanced utilization of computing resources of nodes and improve the stability of the system. A residential area in Nanjing is taken as an example to design simulation experiments. The results show that the proposed edge nodes deployment method can effectively reduce the data transmission costs of residential nodes. Also,the task migration algorithm can effectively balance the computing resources among edge devices and improve execution efficiency of edge computing services.