Biblio

This study has built a simulation of a smart home system by the Alibaba ECS. The architecture of hardware was based on edge computing technology. The whole method would design a clear classifier to find the boundary between regular and mutation codes. It could be applied in the detection of the mutation code of network. The project has used the dataset vector to divide them into positive and negative type, and the final result has shown the RBF-function SVM method perform best in this mission. This research has got a good network security detection in the IoT systems and increased the applications of machine learning.

The intelligent production line is a complex application with a large number of independent equipment network integration. In view of the characteristics of CPS, the existing modeling methods cannot well meet the application requirements of large scale high-performance system. a formal simulation verification framework and verification method are designed for the performance constraints such as the real-time and security of the intelligent production line based on soft bus. A model-based service-oriented integration approach is employed, which adopts a model-centric way to automate the development course of the entire software life cycle. Developing experience indicate that the proposed approach based on the formal modeling and verification framework in this paper can improve the performance of the system, which is also helpful to achieve the balance of the production line and maintain the reasonable use rate of the processing equipment.