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Achieving predictable and low end-to-end latency for a network of smart services

Millnert, Victor LU ; Eker, Johan LU and Bini, Enrico (2019) IEEE GLOBECOM 2018
Abstract
To remain competitive in the field of manufacturing today, companies must constantly improve the automation loops within their production plants. This can be done by augmenting the automation applications with "smart services" such as supervisory-control applications or machine-learning inference algorithms. The downside is that these smart services are often hosted in a cloud infrastructure and the automation applications require a low and predictable end-to-end latency. However, with the 5G technology it will become possible to establish a low-latency connection to the cloud infrastructure and with proper control of the capacity of the smart services, it will become possible to achieve a low and predictable end-to-end latency for the... (More)
To remain competitive in the field of manufacturing today, companies must constantly improve the automation loops within their production plants. This can be done by augmenting the automation applications with "smart services" such as supervisory-control applications or machine-learning inference algorithms. The downside is that these smart services are often hosted in a cloud infrastructure and the automation applications require a low and predictable end-to-end latency. However, with the 5G technology it will become possible to establish a low-latency connection to the cloud infrastructure and with proper control of the capacity of the smart services, it will become possible to achieve a low and predictable end-to-end latency for the augmented automation applications.

In this work we address the challenge of controlling the capacity of the smart services in a way that achieves a low and predictable end-to-end latency. We do this by deriving a mathematical framework that models a network of smart services that is hosting several automation applications. We propose a generalized AutoSAC (automatic service- and admission controller) that builds on previous work by the authors. In the previous work the system was only capable of handling a single set of smart services, with a single application hosted on top of it. With the contributions of this paper it becomes possible to host multiple applications on top of a larger, more general network of smart services.
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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Automation, Cloud computing, Mathematical Model, Virtual Machining, 3G mobile communication, Uncertainty, Manufacturing
host publication
2018 IEEE Global Communications Conference (GLOBECOM)
pages
7 pages
conference name
IEEE GLOBECOM 2018
conference dates
2018-12-09 - 2018-12-13
external identifiers
  • scopus:85063514071
ISBN
978-1-5386-4727-1
DOI
10.1109/GLOCOM.2018.8647332
language
English
LU publication?
yes
id
594f4613-8be7-4554-82d8-0e5e5de0dde4
date added to LUP
2018-11-14 00:14:31
date last changed
2019-10-23 06:02:23
@inproceedings{594f4613-8be7-4554-82d8-0e5e5de0dde4,
  abstract     = {To remain competitive in the field of manufacturing today, companies must constantly improve the automation loops within their production plants. This can be done by augmenting the automation applications with "smart services" such as supervisory-control applications or machine-learning inference algorithms. The downside is that these smart services are often hosted in a cloud infrastructure and the automation applications require a low and predictable end-to-end latency. However, with the 5G technology it will become possible to establish a low-latency connection to the cloud infrastructure and with proper control of the capacity of the smart services, it will become possible to achieve a low and predictable end-to-end latency for the augmented automation applications.<br/><br/>In this work we address the challenge of controlling the capacity of the smart services in a way that achieves a low and predictable end-to-end latency. We do this by deriving a mathematical framework that models a network of smart services that is hosting several automation applications. We propose a generalized AutoSAC (automatic service- and admission controller) that builds on previous work by the authors. In the previous work the system was only capable of handling a single set of smart services, with a single application hosted on top of it. With the contributions of this paper it becomes possible to host multiple applications on top of a larger, more general network of smart services.<br/>},
  author       = {Millnert, Victor and Eker, Johan and Bini, Enrico},
  isbn         = {978-1-5386-4727-1},
  keyword      = {Automation,Cloud computing,Mathematical Model,Virtual Machining,3G mobile communication,Uncertainty,Manufacturing},
  language     = {eng},
  pages        = {7},
  title        = {Achieving predictable and low end-to-end latency for a network of smart services},
  url          = {http://dx.doi.org/10.1109/GLOCOM.2018.8647332},
  year         = {2019},
}