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Latency prediction in 5G for control with deadtime compensation

Ruuskanen, Johan LU orcid ; Peng, Haorui LU orcid and Martins, Alexandre LU orcid (2019) p.51-55
Abstract
With the promise of increased responsiveness and robustness of the emerging 5G technology, it is suddenly becoming feasible to deploy latency-sensitive control systems over the cloud via a mobile network. Even though 5G is herald to give lower latency and jitter than current mobile networks, the effect of the delay would still be non-negligible for certain applications.

In this paper we explore and demonstrate the possibility of compensating for the unknown and time-varying latency introduced by a 5G mobile network for control of a latency-sensitive plant. We show that the latency from a prototype 5G test bed lacks significant short-term correlation, making accurate latency prediction a difficult task. Further, because of the... (More)
With the promise of increased responsiveness and robustness of the emerging 5G technology, it is suddenly becoming feasible to deploy latency-sensitive control systems over the cloud via a mobile network. Even though 5G is herald to give lower latency and jitter than current mobile networks, the effect of the delay would still be non-negligible for certain applications.

In this paper we explore and demonstrate the possibility of compensating for the unknown and time-varying latency introduced by a 5G mobile network for control of a latency-sensitive plant. We show that the latency from a prototype 5G test bed lacks significant short-term correlation, making accurate latency prediction a difficult task. Further, because of the unknown and time-varying latency our used simple interpolation-based model experiences some troubling theoretical properties, limiting its usability in real world environments. Despite this, we give a demonstration of the strategy which seems to increase robustness in a simulated plant.
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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Latency prediction, 5G, Deadtime compensation, Time varying delay
host publication
IoT-Fog '19 Proceedings of the Workshop on Fog Computing and the IoT
pages
4 pages
publisher
Association for Computing Machinery (ACM)
external identifiers
  • scopus:85066038059
ISBN
978-1-4503-6698-4
project
Autonomous camera systems in resource constrained environments
Event-Based Information Fusion for the Self-Adaptive Cloud
language
English
LU publication?
yes
id
a08df584-b5c6-4ec2-8852-7b7459a60928
date added to LUP
2019-06-11 10:47:44
date last changed
2022-05-03 22:07:40
@inproceedings{a08df584-b5c6-4ec2-8852-7b7459a60928,
  abstract     = {{With the promise of increased responsiveness and robustness of the emerging 5G technology, it is suddenly becoming feasible to deploy latency-sensitive control systems over the cloud via a mobile network. Even though 5G is herald to give lower latency and jitter than current mobile networks, the effect of the delay would still be non-negligible for certain applications.<br/><br/>In this paper we explore and demonstrate the possibility of compensating for the unknown and time-varying latency introduced by a 5G mobile network for control of a latency-sensitive plant. We show that the latency from a prototype 5G test bed lacks significant short-term correlation, making accurate latency prediction a difficult task. Further, because of the unknown and time-varying latency our used simple interpolation-based model experiences some troubling theoretical properties, limiting its usability in real world environments. Despite this, we give a demonstration of the strategy which seems to increase robustness in a simulated plant.<br/>}},
  author       = {{Ruuskanen, Johan and Peng, Haorui and Martins, Alexandre}},
  booktitle    = {{IoT-Fog '19 Proceedings of the Workshop on Fog Computing and the IoT}},
  isbn         = {{978-1-4503-6698-4}},
  keywords     = {{Latency prediction; 5G; Deadtime compensation; Time varying delay}},
  language     = {{eng}},
  month        = {{04}},
  pages        = {{51--55}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{Latency prediction in 5G for control with deadtime compensation}},
  url          = {{https://lup.lub.lu.se/search/files/65822795/fogIoT_ruuskanen.pdf}},
  year         = {{2019}},
}