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Computer Communications
Article . 2025 . Peer-reviewed
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Article . 2024 . Peer-reviewed
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Automating 5G network slice management for industrial applications

Authors: Perdigão, André; Quevedo, José; Aguiar, Rui L.;

Automating 5G network slice management for industrial applications

Abstract

The transition to Industry 4.0 introduces new use cases with unique communication requirements, demanding wireless technologies capable of dynamically adjusting their performance to meet various demands. Leveraging network slicing, 5G technology offers the flexibility to support such use cases. However, the usage and deployment of network slices in networks are complex tasks. To increase the adoption of 5G, there is a need for mechanisms that automate the deployment and management of network slices. This paper introduces a design for a network slice manager capable of such mechanisms in 5G networks. This design adheres to related standards, facilitating interoperability with other software, while also considering the capabilities and limitations of the technology. The proposed design can provision custom slices tailored to meet the unique requirements of verticals, offering communication performance across the spectrum of the three primary 5G services (eMBB, URLLC, and mMTC/mIoT). To access the proposed design, a Proof-of-Concept (PoC) prototype was developed and evaluated. The evaluation results demonstrate the flexibility of the proposed solution for deploying slices adjusted to the vertical use cases. Additionally, the slices generated by the PoC maintain a high TRL (Technology Readiness Level) equivalent to that of the commercial-graded network used.

Keywords

Industrial IoT, Testbed, Private 5G networks, Industry 4.0, Network slicing

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    selected citations
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    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).
    11
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
11
Top 10%
Top 10%
Top 10%
hybrid