Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-24730
Publication type: Conference paper
Type of review: Peer review (publication)
Title: AI-powered Infrastructures for intelligence and automation in beyond-5G systems
Authors: Militano, Leonardo
Zafeiropoulos, Anastasios
Fotopoulou, Eleni
Bruschi, Roberto
Lombardo, Chiara
Edmonds, Andy
Papavassiliou, Symeon
et. al: No
DOI: 10.1109/GCWkshps52748.2021.9682117
10.21256/zhaw-24730
Proceedings: Proceedings of 2021 IEEE Globecom Workshops (GC Wkshps)
Page(s): 1
Pages to: 6
Conference details: 2021 IEEE Globecom Workshops (GC Wkshps), Madrid, Spain, 7-11 December 2021
Issue Date: Jan-2022
Publisher / Ed. Institution: IEEE
ISBN: 978-1-6654-2390-8
Language: English
Subjects: 6G system; Federated learning; Artificial Intelligence; Reinforcement learning; Blockchain; Automated orchestration; Edge computing; Cloud-native
Subject (DDC): 006: Special computer methods
621.3: Electrical, communications, control engineering
Abstract: In this paper, a vision for beyond-5G systems is proposed where automation, intelligence and data privacy in cloudnative infrastructures are in focus. Exploiting the convergence of cloud technologies at the edge and mobile communication networks, a set of architectural and technological solutions is discussed that will play a fundamental role on the path from 5G towards future sixth-generation systems. Currently, a strong need is felt in the telecommunication world for greater automation to meet the extreme requirements expected for future 6G applications. In this regard, Artificial Intelligence (AI) is gaining high momentum as one of the central enabling technologies for beyond-5G networks. Reinforcement Learning (RL) and Federated Learning (FL) are here proposed as technologies to enhance network automation and enable privacy-aware applications. Blockchain is proposed as a solution for non-repudiation and trustworthiness in the AI pipelines. These technologies are brought together in a comprehensive cloud-native architectural vision to fill the gap between current 5G systems and AI-powered secure systems of the future.
URI: https://digitalcollection.zhaw.ch/handle/11475/24730
Fulltext version: Accepted version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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