Service scheduling based on edge computing for power distribution IoT

Abstract

With the growing amounts of multi-micro grids, electric vehicles, smart home, smart cities connected to the Power Distribution Internet of Things (PD-IoT) system, greater computing resource and communication bandwidth are required for power distribution. It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence. This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT. The architecture, components and functional requirements of the PD-IoT with edge computing platform are proposed. Then, the structure of the service scheduling system is presented. Further, a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method. The validity of the method is evaluated by simulation tests. Results indicate that the mean load balancing ratio is reduced by 99.16% and the optimized offloading links can be acquired within 1.8 iterations. Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.