Hierarchical Network Data Analytics Framework for B5G Network
  Automation: Design and Implementation
Youbin Jeon Sangheon Pack
5G introduced modularized network functions (NFs) to support emerging
services in a more flexible and elastic manner. To mitigate the complexity in
such modularized NF management, automated network operation and management are
indispensable, and thus the 3rd generation partnership project (3GPP) 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. 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.