Infrastructure-wide and intent-based networking dataset for 5G-and-beyond AI-driven autonomous networks

Abstract

In the era of Autonomous Networks (ANs), artificial intelligence (AI) plays a crucial role for their development in cellular networks, especially in 5G-and-beyond networks. The availability of high-quality networking datasets is one of the essential aspects for creating data-driven algorithms in network management and optimisation tasks. These datasets serve as the foundation for empowering AI algorithms to make informed decisions and optimise network resources efficiently. In this research work, we propose the IW-IB-5GNET networking dataset: an infrastructure-wide and intent-based dataset that is intended to be of use in research and development of network management and optimisation solutions in 5G-and-beyond networks. It is infrastructure wide due to the fact that the dataset includes information from all layers of the 5G network. It is also intent based as it is initiated based on predefined user intents. The proposed dataset has been generated in an emulated 5G network, with a wide deployment of network sensors for its creation. The IW-IB-5GNET dataset is promising to facilitate the development of autonomous and intelligent network management solutions that enhance network performance and optimisation.

Publication DOI: https://doi.org/10.3390/s24030783
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Aston University (General)
Funding Information: This research was funded by the European Commission under two projects: RIGOUROUS (secuRe desIGn and deplOyment of trUsthwoRthy cOntinUum computing 6G Services) and ARCADIAN-IoT (Autonomous Trust, Security and Privacy Management Framework for IoT) grant n
Additional Information: Copyright © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: networking dataset,network control rules,network management,network optimisation,5G,intent-based networking
Publication ISSN: 1424-8220
Last Modified: 18 Apr 2025 07:25
Date Deposited: 15 Apr 2025 14:48
Full Text Link:
Related URLs: https://www.mdp ... 4-8220/24/3/783 (Publisher URL)
PURE Output Type: Article
Published Date: 2024-02
Published Online Date: 2024-01-25
Accepted Date: 2024-01-23
Authors: Andrade-Hoz, Jimena
Wang, Qi
Alcaraz-Calero, Jose M. (ORCID Profile 0000-0002-2654-7595)

Download

[img]

Version: Published Version

License: Creative Commons Attribution


Export / Share Citation


Statistics

Additional statistics for this record