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Towards intelligent Industry 4.0 5G networks: A first throughput and QoE measurement campaign

Tärneberg, William LU ; Hamsis, Omar ; Hedlund, Johan ; Brunnström, Kjell ; Fitzgerald, Emma LU orcid ; Johnsson, Andreas ; Berggren, Victor ; Kihl, Maria LU ; Rao, Akhila and Steinert, Rebecca , et al. (2020) 28 th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
Abstract
5G promises to usher in the industrial 4.0 era. In that era, intricately managed autonomous industrial sites with for example remotely controller equipment and autonomous units promise previously unseen levels of efficiency. Although such scenarios are elusive, they come with strict long-since established safety requirements. To uphold such requirements, intelligent industrial 5G networks, that actively take into account prevailing conditions and dynamics of the workers on the site, the equipment, and the network, are needed. Little is known about the dynamics of actual industrial 5G networks and the interplay between network performance and QoE. In this paper, as a step towards intelligent industrial 5G networks, we measure network... (More)
5G promises to usher in the industrial 4.0 era. In that era, intricately managed autonomous industrial sites with for example remotely controller equipment and autonomous units promise previously unseen levels of efficiency. Although such scenarios are elusive, they come with strict long-since established safety requirements. To uphold such requirements, intelligent industrial 5G networks, that actively take into account prevailing conditions and dynamics of the workers on the site, the equipment, and the network, are needed. Little is known about the dynamics of actual industrial 5G networks and the interplay between network performance and QoE. In this paper, as a step towards intelligent industrial 5G networks, we measure network performance for an industrial 5G network, and conduct QoE experiments with remote controlled industrial equipment on an operational site. The results revealed unexpected relationships between QoE and network performance that shows how important domain-specific knowledge is when researching intelligent industrial 5G networks. (Less)
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author
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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
28 th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
conference location
Hvar, Croatia
conference dates
2020-09-17 - 2020-09-19
external identifiers
  • scopus:85096583685
ISBN
978-1-7281-7538-6
978-953-290-099-6
DOI
10.23919/SoftCOM50211.2020.9238299
project
Cyber Security for Next Generation Factory (SEC4FACTORY)
E! Celtic-Plus 5G PERFECTA
language
English
LU publication?
yes
id
00eeb69e-59e3-42fe-a8f2-cdf51331f0f9
date added to LUP
2020-06-11 11:09:13
date last changed
2024-06-13 17:25:14
@inproceedings{00eeb69e-59e3-42fe-a8f2-cdf51331f0f9,
  abstract     = {{5G promises to usher in the industrial 4.0 era. In that era, intricately managed autonomous industrial sites with for example remotely controller equipment and autonomous units promise previously unseen levels of efficiency. Although such scenarios are elusive, they come with strict long-since established safety requirements. To uphold such requirements, intelligent industrial 5G networks, that actively take into account prevailing conditions and dynamics of the workers on the site, the equipment, and the network, are needed. Little is known about the dynamics of actual industrial 5G networks and the interplay between network performance and QoE. In this paper, as a step towards intelligent industrial 5G networks, we measure network performance for an industrial 5G network, and conduct QoE experiments with remote controlled industrial equipment on an operational site. The results revealed unexpected relationships between QoE and network performance that shows how important domain-specific knowledge is when researching intelligent industrial 5G networks.}},
  author       = {{Tärneberg, William and Hamsis, Omar and Hedlund, Johan and Brunnström, Kjell and Fitzgerald, Emma and Johnsson, Andreas and Berggren, Victor and Kihl, Maria and Rao, Akhila and Steinert, Rebecca and Kilic, Caner}},
  booktitle    = {{2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)}},
  isbn         = {{978-1-7281-7538-6}},
  language     = {{eng}},
  month        = {{06}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Towards intelligent Industry 4.0 5G networks: A first throughput and QoE measurement campaign}},
  url          = {{http://dx.doi.org/10.23919/SoftCOM50211.2020.9238299}},
  doi          = {{10.23919/SoftCOM50211.2020.9238299}},
  year         = {{2020}},
}