Intent-Based Network Policy Generation for Knowledge Definition

To achieve on-demand services in all scenarios in the sixth-generation mobile communication system, the complexity and diversity of networks and services greatly affect the reliability and robustness of existing methods. Therefore, a framework that combines intent translation and network slicing is proposed for universal application in all scenarios. Firstly, given the diversity of services, a multi-step intent translation method that utilizes external knowledge and deep learning is proposed. Secondly, a multi-path resource scheduling algorithm based on mixed integer linear programming is presented to improve the overall utilization of network resources and effectively respond to changes in network environments. Experimental results have demonstrated that the proposed framework can achieve accurate division of business resources based on multi-tenant intent to ensure user experience and provide on-demand services in all scenarios. © 2024 Beijing University of Posts and Telecommunications. All rights reserved.