Edge-Cloud Alarm Level of Heterogeneous IIoT Devices Based on Knowledge Distillation in Smart Manufacturing

Abstract

Along with the fourth industrial revolution, smart factories are receiving a great deal of attention. Large volumes of real-time data that are generated at high rates, especially in industries, are becoming increasingly important. Accordingly, the Industrial Internet of Things (IIoT), which connects, controls, and communicates with heterogeneous devices, is important to industrial sites and is now indispensable. To ensure the fairness and quality of the IIoT with limited network resources, the network connection of the IIoT needs to be constructed more intelligently. Many studies are being conducted on the efficient use of the resources that are imposed on IIoT devices. Therefore, in this paper, we propose a collaboration optimization method for heterogeneous devices that is based on cloud–fog–edge architecture. First, this paper proposes a knowledge distillation-based algorithm that can collaborate on cloud–fog–edge computing on the basis of distributed control. Second, to compensate for the shortcomings of knowledge distillation, we propose a framework for combining a soft-label-based alarm level. Finally, the method that is proposed in this paper was verified through several experiments, and it is shown that this method can effectively shorten the response time and solve the problems of existing IIoT networks, and that it can be efficiently applied to heterogeneous devices.