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Soft Computing
Published in: Soft Computing 13/2020

30-10-2019 | Methodologies and Application

5GAuNetS: an autonomous 5G network selection framework for Industry 4.0

Authors: Bhanu Priya, Jyoteesh Malhotra

Published in: Soft Computing | Issue 13/2020

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Abstract

The megatrends within the industrial automation and global value chains expedited the adoption of “Industry 4.0 enabled by 5G” to comprehend extremely flexible and smart production systems. The pivotal challenge for the smart manufacturing leveraging on 5G is the seamless vertical handover and connectivity to a suitable network in accordance with the determined application. The existing literature reports numerous strategies to ensure “always best connected” paradigm but they suffer from a couple of limitations. The amateurish approach employed in these strategies propelled the development of an autonomous network selection model exploiting fuzzy analytical hierarchical process consolidated with the novel extended efficacy coefficient method-based Technique for Order Preference by Similarity to Ideal Solution. This article addresses the vertical handover execution under the circumstances of four typical 5G application scenarios, respectively, i.e. Tactile Internet, Bitpipe, Internet of Things and Internet Access for Regional Areas. The analytical results validated through the extensive simulation revealed that the proposed hybrid scheme is effective and efficient compared to other methods in terms of avoiding the unnecessary handover and the ranking abnormality issues.
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Metadata
Title
5GAuNetS: an autonomous 5G network selection framework for Industry 4.0
Authors
Bhanu Priya
Jyoteesh Malhotra
Publication date
30-10-2019
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 13/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04460-y

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