A resource scheduling algorithm in edge computing for smart factory applications

Resource scheduling is essential to improve the efficiency of edge computing. This paper studies the resource scheduling problem for smart factory applications. Considering the task execution is constrained by the strict production process in plant field, the resource scheduling problem is formalized taking both task execution time and resource balance as the optimization objectives. Then an improved NSGA-II algorithm is proposed and deployed in Kubernetes tools. The simulation results based on the simulation microservice of sock shop factory showed that, compared with the baseline algorithms, the proposed algorithm can effectively reduce the task execution time and improve the resource balance between edge nodes.