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5Growth: An End-to-End Service Platform for Automated Deployment and Management of Vertical Services over 5G Networks

Authors: Xi Li 0002; Andres Garcia-Saavedra; Xavier Pérez Costa; Carlos J. Bernardos; Carlos Guimarães; Kiril Antevski; Josep Mangues-Bafalluy; +11 Authors

5Growth: An End-to-End Service Platform for Automated Deployment and Management of Vertical Services over 5G Networks

Abstract

This article introduces the key innovations of the 5Growth service platform to empower verticals industries with an AI-driven automated 5G End-to-End (E2E) slicing solution which allows industries to achieve their service requirements. Specifically, we present multiple vertical pilots (Industry 4.0, Transportation and Energy), identify the key 5G requirements to enable them and analyze existing technical and functional gaps as compared to current solutions. Based on the identified gaps, we propose a set of innovations to address them with: (i) support of 3GPP-based RAN slices by introducing a RAN slicing model and providing automated RAN orchestration and control, (ii) an AI-driven closed-loop for automated service management with Service Level Agreement (SLA) assurance, and, (iii) Multi-domain solutions to expand service offerings by aggregating services and resources from different provider domains and also enable the integration of private 5G networks with public networks.

Digital Object Identifier: 10.1109/MCOM.2009.5273797

Keywords

Market research, Telecomunicaciones, NO KEYWORDS, 5G mobile communication, Transportation, Technological innovation, 5G Mobile communication, Service level agreements

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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58
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21
99
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