Fragmentation and isolation technology of power communication network based on FlexE

Abstract

In the electric power communication network architecture, the Internet of Things business requirements of mutual perception and coordination of each link, and the traditional security protection structure based on boundary isolation, it is a difficult point to achieve a high degree of compatibility and coupling. Therefore, when PCE performs path calculation in the multi-domain FlexE network, it is necessary to consider the delay of the transmission path. The low-delay transmission of the service is ensured. This paper analyzes the network-slicing requirements of typical business scenarios in the power grid. In view of the hierarchical architecture of the power Internet of Things, this paper analyzes its requirements for 5G technology and network slicing, and the overall architecture of the integrated energy Internet. Finally, according to the current business needs, this paper proposes a power slicing scheme that meets the needs of the power grid's various business scenarios. On this basis, an end-to-end network architecture based on power slicing is designed. The results verify that the safe and efficient slicing strategy based on deep reinforcement learning has better performance than the traditional machine learning model, which can enhance the monitoring effect of the terminal network security of the power Internet of Things. It can also improve the terminal security of the power Internet of Things at this stage and can detect the potential risks of terminal security monitoring.