Hierarchical Network Data Analytics Framework for 6G Network Automation: Design and Implementation

To mitigate the complexity of modularized network function (NF) management in 5G, automated network operation and management are indispensable, and, therefore, the 3rd Generation Partnership Project has introduced a network data analytics function (NWDAF). However, a conventional NWDAF needs to conduct both inference and training tasks, and, thus, it is difficult to provide the analytics results to NFs in a timely manner for an increased number of analytics requests. In this article, we propose a hierarchical network data analytics framework (H-NDAF) where inference tasks are distributed to multiple leaf NWDAFs, and training tasks are conducted at the root NWDAF. H-NDAF provides timely inference results while maintaining high accuracy. Furthermore, we present a use case to optimize the policy for user equipment data flows. Extensive simulation results using open source software (i.e., free5GC) demonstrate that H-NDAF can provide sufficiently accurate analytics and faster analytics provision time compared to the conventional NWDAF.