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NWDAMaaS: A Containerized Real-Time Data Analytic Framework for 5G Self-Organizing Networks.

Authors :
Wang, Zhaoning
Cheng, Xinzhou
Lyu, Feibi
Zhu, Jiajia
Li, Zhidu
Cheng, Bo
Source :
MobiCom: International Conference on Mobile Computing & Networking; 2023, p1-3, 3p
Publication Year :
2023

Abstract

With the 5G commercial deployments rapidly proceeding, operating mobile networks efficiently has become a great challenge. Self-organizing networks have been proposed to focus on automatically monitoring, analyzing and optimizing networks. Regarding the growing scale and complexity, 5G self-organizing networks confront the challenge to handle the massive data. Therefore, AI models are urgently needed to enable end-to-end network automation. In this demonstration, benefiting from the open data interfaces of the standardized NWDAF within the 5GC network, we implement a containerized network data analytic framework embedding Docker-based AI model containers into 5G networks. Furthermore, we simulate a use case automatically monitoring and optimizing user-level QoE in real time and simulation results are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15435679
Database :
Complementary Index
Journal :
MobiCom: International Conference on Mobile Computing & Networking
Publication Type :
Conference
Accession number :
180031908
Full Text :
https://doi.org/10.1145/3570361.3614076