Demo: AI-Engine Enabled Intelligent Management in B5G/6G Networks

Abstract

In the B5G and 6G era, service demands of diverse vertical industries are becoming increasingly complex and intelligence has become the development trend of wireless networks. By means of network slicing, resources of the infrastructure can be shared by multiple services with differentiated quality of service (QoS) guarantees. However, the uncertainty and dynamics on real-time network status requires an intelligent management scheme. Artificial intelligence (AI) algorithms are urgently needed in slice management to improve resource utilization and quickly satisfy the resource requirements of different services. This demo shows how an AI-Engine that encapsulates multiple AI algorithms can contribute to the life-cycle management of slices. In particular, our solution considers distributed deployment of the AI-Engine and provides different machine learning (ML) models for various use cases. This also enables the AI-Engine to support data analysis of network functions and intelligent applications in the edge cloud. Furthermore, this solution allows to adjust computing resource allocation for each distributed component of the AI-Engine to facilitate the intelligent network management.