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 | Size | Format | |
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S-JNL-VOL3.ISSUE3-2022-A53-PDF-E.pdf | 1,6 MB | Adobe PDF | View/Open |
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