DEEP : A Vertical-Oriented Intelligent and Automated Platform for the Edge and Fog
(2021) In IEEE Communications Magazine 59(6). p.66-72- Abstract
The fifth generation (5G) of mobile communications introduces improvements on many fronts when compared to its previous generations. Besides the performance enhancements and new advances in radio technologies, it also integrates other technological domains, such as cloud-to-things continuum and artificial intelligence. In this work, the 5G-DIVE Elastic Edge Platform (DEEP) is proposed as the linking piece for the integration of these technological domains, making available an intelligent edge and fog 5G end-to-end solution. This solution brings numerous benefits to vertical industries by enabling streamlined, abstracted, and automated management of their vertical services, thus contributing to the introduction of novel services, cost... (More)
The fifth generation (5G) of mobile communications introduces improvements on many fronts when compared to its previous generations. Besides the performance enhancements and new advances in radio technologies, it also integrates other technological domains, such as cloud-to-things continuum and artificial intelligence. In this work, the 5G-DIVE Elastic Edge Platform (DEEP) is proposed as the linking piece for the integration of these technological domains, making available an intelligent edge and fog 5G end-to-end solution. This solution brings numerous benefits to vertical industries by enabling streamlined, abstracted, and automated management of their vertical services, thus contributing to the introduction of novel services, cost savings, and improved time to market. Preliminary validation of the proposed platform is performed through a proof of concept, along with a qualitative analysis of its benefits for Industry 4.0 and autonomous drone scouting vertical industries.
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- author
- Guimaraes, Carlos ; Groshev, Milan ; Cominardi, Luca ; Zabala, Aitor ; Contreras, Luis M. ; Talat, Samer T. ; Zhang, Chao LU ; Hazra, Saptarshi ; Mourad, Alain and De La Oliva, Antonio
- organization
- publishing date
- 2021-06-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Communications Magazine
- volume
- 59
- issue
- 6
- article number
- 9475161
- pages
- 7 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85112217943
- ISSN
- 0163-6804
- DOI
- 10.1109/MCOM.001.2000986
- language
- English
- LU publication?
- yes
- id
- 53b97d39-59e9-4eb3-aebc-fb2087041a3a
- date added to LUP
- 2021-09-20 13:58:46
- date last changed
- 2022-04-27 03:58:53
@article{53b97d39-59e9-4eb3-aebc-fb2087041a3a, abstract = {{<p>The fifth generation (5G) of mobile communications introduces improvements on many fronts when compared to its previous generations. Besides the performance enhancements and new advances in radio technologies, it also integrates other technological domains, such as cloud-to-things continuum and artificial intelligence. In this work, the 5G-DIVE Elastic Edge Platform (DEEP) is proposed as the linking piece for the integration of these technological domains, making available an intelligent edge and fog 5G end-to-end solution. This solution brings numerous benefits to vertical industries by enabling streamlined, abstracted, and automated management of their vertical services, thus contributing to the introduction of novel services, cost savings, and improved time to market. Preliminary validation of the proposed platform is performed through a proof of concept, along with a qualitative analysis of its benefits for Industry 4.0 and autonomous drone scouting vertical industries. </p>}}, author = {{Guimaraes, Carlos and Groshev, Milan and Cominardi, Luca and Zabala, Aitor and Contreras, Luis M. and Talat, Samer T. and Zhang, Chao and Hazra, Saptarshi and Mourad, Alain and De La Oliva, Antonio}}, issn = {{0163-6804}}, language = {{eng}}, month = {{06}}, number = {{6}}, pages = {{66--72}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Communications Magazine}}, title = {{DEEP : A Vertical-Oriented Intelligent and Automated Platform for the Edge and Fog}}, url = {{http://dx.doi.org/10.1109/MCOM.001.2000986}}, doi = {{10.1109/MCOM.001.2000986}}, volume = {{59}}, year = {{2021}}, }