KID: Knowledge Graph-Enabled Intent-Driven Network with Digital Twin

To meet novel services and networking requirements towards the next generation applications, intent-driven network is proposed as a promising networking paradigm. It is with capabilities of intent refinement, policy generation, and state awareness. And these distinctive capabilities contribute to its wide applications to the next generation networks. However, current researches lack a generalization model of intent refinement. Additionally, it is difficult to extract available knowledge from huge raw data of the network status, and guarantee the precise generation of network policies. To solve these challenges, we present a knowledge graph-enabled intent-driven network with the digital twin, which is termed as KID in this work. In the KID, knowledge graph is utilized to represent user intents, abstract network status, and express network policies. And the digital twin is applied to validate intents as well as abstract the physical network. The KID enhances the capabilities of intent-driven networks to refine intents, contributing to the continuous assurance of accurate intent fulfillment. Finally, we present a proof of concept implementation of the KID. Simulation results verify the feasibility and effectiveness of the presented KID framework.