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Latency-aware Radio Resource Allocation over Cloud RAN for Industry 4.0

Peng, Haorui LU orcid ; Tärneberg, William LU and Kihl, Maria LU (2021) 30th International Conference on Computer Communications and Networks (ICCCN 2021)
Abstract
The notion of Cloud RAN is taking a prominent role in narrative for the next generation wireless infrastructure. It is also seen as a mean to industrial communication systems. In order to provide reliable wireless connectivity for industrial deployments, by conventional means, the cloud infrastructure needs to be reliable and incur little latency, which however, is contradictory to the stochastic nature of cloud infrastructures. In this paper, we investigate the impact of stochastic delay on a radio resource allocation process deployed in Cloud RAN. We proceed to propose a strategy for realizing timely cloud responses and then adapt that strategy to a radio resource allocation problem. Further, we evaluate the strategies in an industrial... (More)
The notion of Cloud RAN is taking a prominent role in narrative for the next generation wireless infrastructure. It is also seen as a mean to industrial communication systems. In order to provide reliable wireless connectivity for industrial deployments, by conventional means, the cloud infrastructure needs to be reliable and incur little latency, which however, is contradictory to the stochastic nature of cloud infrastructures. In this paper, we investigate the impact of stochastic delay on a radio resource allocation process deployed in Cloud RAN. We proceed to propose a strategy for realizing timely cloud responses and then adapt that strategy to a radio resource allocation problem. Further, we evaluate the strategies in an industrial IoT scenario using a simulated environment. Experimentation shows that, with our proposed strategy, a significant performance improvement on timely responses can be achieved even with noisy cloud environment. Improvements in resource utilization can be also attained for a resource allocation process deployed over Cloud RAN with this strategy. (Less)
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
host publication
2021 International Conference on Computer Communications and Networks (ICCCN)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
30th International Conference on Computer Communications and Networks (ICCCN 2021)
conference location
Athens, Greece
conference dates
2021-07-19 - 2021-07-22
external identifiers
  • scopus:85114963498
ISBN
978-1-6654-4835-2
978-1-6654-1278-0
DOI
10.1109/ICCCN52240.2021.9522200
language
English
LU publication?
yes
id
c6307d23-659e-4629-87ea-4af7b7f1e311
date added to LUP
2021-09-06 11:04:33
date last changed
2024-06-29 16:48:20
@inproceedings{c6307d23-659e-4629-87ea-4af7b7f1e311,
  abstract     = {{The notion of Cloud RAN is taking a prominent role in narrative for the next generation wireless infrastructure. It is also seen as a mean to industrial communication systems. In order to provide reliable wireless connectivity for industrial deployments, by conventional means, the cloud infrastructure needs to be reliable and incur little latency, which however, is contradictory to the stochastic nature of cloud infrastructures. In this paper, we investigate the impact of stochastic delay on a radio resource allocation process deployed in Cloud RAN. We proceed to propose a strategy for realizing timely cloud responses and then adapt that strategy to a radio resource allocation problem. Further, we evaluate the strategies in an industrial IoT scenario using a simulated environment. Experimentation shows that, with our proposed strategy, a significant performance improvement on timely responses can be achieved even with noisy cloud environment. Improvements in resource utilization can be also attained for a resource allocation process deployed over Cloud RAN with this strategy.}},
  author       = {{Peng, Haorui and Tärneberg, William and Kihl, Maria}},
  booktitle    = {{2021 International Conference on Computer Communications and Networks (ICCCN)}},
  isbn         = {{978-1-6654-4835-2}},
  language     = {{eng}},
  month        = {{07}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Latency-aware Radio Resource Allocation over Cloud RAN for Industry 4.0}},
  url          = {{https://lup.lub.lu.se/search/files/102069812/conference_101719.pdf}},
  doi          = {{10.1109/ICCCN52240.2021.9522200}},
  year         = {{2021}},
}