An Intent-based Network Empowered by Knowledge Graph: Enhancement of Intent Translation and Management Function for Vertical Industry

In recent years, Intent-based Networks (IBNs) have emerged as an effective approach for managing and optimizing complicated networks. However, contemporary IBN systems continue to struggle with understanding user intent and converting it into network configurations. To address this problem, this research presents an intent-based network empowered by knowledge graph (IBN-KG), which combines knowledge graph technology with IBN to enhance intent translation and management. We concentrate on the construction of a knowledge graph for grid scenarios and its application to improve IBN performance. The paper also introduces a tailored Knowledge Graph construction scheme for vertical industry applications, focusing on smart grid scenarios. This involves a distinct data layer, knowledge extraction through natural language processing, knowledge fusion, knowledge updating, and knowledge application through user interfaces. In summary, the integration of Knowledge Graph technology with IBN promises a more intelligent, flexible, and effective way of translating and managing user intent in network configurations, with particular emphasis on applications in smart grid scenarios.