Network Digital Twins for 6G: Defining Data Taxonomy and Data Models

Auteurs

Zaki-Hindi A., Sottet J.S., Turcanu I., Faye S.

Référence

2024 IEEE Conference on Standards for Communications and Networking, CSCN 2024, pp. 124-128, 2024

Description

As the telecommunications industry moves towards 6G, Network Digital Twins (NDTs) have emerged as a useful means for real-time monitoring, automation, and performance optimization in next-generation networks. This paper contributes to the ongoing research on NDTs within the framework of the 6G-TWIN project by presenting a comprehensive vision for NDT architecture and establishing baseline definitions for NDT data models, i.e., basic and functional models. We propose a structured taxonomy for the data required by these models to ensure a shared semantics consistent with existing standards. Furthermore, we introduce a graph-based modeling approach that provides a foundation for constructing basic models within NDTs, representing the physical network. Lastly, we discuss the challenges related to constructing basic models and propose future directions to address them.

Lien

doi:10.1109/CSCN63874.2024.10849705