Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1553
Title: Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030
Authors: Contreras, Luis M.
Serrano, Javier
Mamatas, Lefteris
Bernini, Giacomo
Monti, Paolo
Antunes, Mario
Atmojo, Udayanto
Tocker, Eli
Val, Inaki
Sgambelluri, Andrea
Harri, Jerome
Lioy, Antonio
Martinez-Julia, Pedro
Gonzalez, Jose
Sanchez-Garrido, Jorge
Asaeda, Hitoshi
Type: Article
Subjects: FRASCATI::Engineering and technology
FRASCATI::Engineering and technology::Other engineering and technologies
Keywords: Architecture
beyond 5G
6G
smartness
Issue Date: Dec-2022
Source: ITU Journal on Future and Evolving Technologies
Volume: 3
Issue: 3
First Page: 693
Last Page: 709
Abstract: The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment.
URI: https://doi.org/10.52953/SAMO3073
https://ruomo.lib.uom.gr/handle/7000/1553
ISSN: 2616-8375
Other Identifiers: 10.52953/SAMO3073
Appears in Collections:Department of Applied Informatics

Files in This Item:
File Description SizeFormat 
S-JNL-VOL3.ISSUE3-2022-A53-PDF-E.pdf1,6 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.