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Resource placement strategy optimization for smart grid application using 5G wireless networks

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 4 (2022)

DOI
10.11591/ijece.v12i4.pp3932-3942
ISSN
2722-2578, 2088-8708
Published
2022-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

With the evolution of 5G-network, wireless mobile networks are growing to take a strong stand in attempts to achieve ubiquitous large-scale acquisition, connectivity and processing. Smart-grids are among the critical areas that can benefit from the capabilities of the 5G-network, especially internet of things (IoT) applications such as massive machine-type-communications or ultra-reliable low-latency communications. A distributed cloud-services use the cloud, fog and edge computing infrastructures and applications to take advantage of every available resource including network equipment and connected objects to optimize cost, energy, and latency depending on the planned optimization criteria. In this article, we present smart-grid solution based on cloud-services and 5G-network, then we study the integration of smart-grid services in the cloud based on: placement in the cloud and in the end-device, and finally we introduce our proposed solution based on Intelligent placement strategy. The scenarios are evaluated by the iFogSim simulator, and the analyzed results compare the standard cloud placement, edge placement and our intelligent placement with regard to the optimization of the energy consumption, latency, and network usage. The findings show that cloud energy consumption can be substantially reduced using Intelligent Placement while respecting the potential central processing unit (CPU) processing power-limit for each IoT-device used and network constraints in smart-grid.

Collaboration network of the authors

19 authors · 67 co-authorship links · 31 across different organisations

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  • Sidi Mohamed Ben Abdellah University
  • Université Moulay Ismail de Meknes
  • Institut National des Postes et Télécommunications
  • Lebanese University
  • Laboratoire d'électronique, systèmes de communication et microsystèmes
  • Université Privée de Fès
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Abdelhafid Es-SaqySidi Mohamed Ben Abdellah University13
Maryam AbataSidi Mohamed Ben Abdellah University9
Mahmoud MehdiLebanese University9
Catherine AlganiLaboratoire d'électronique, systèmes de communication et microsystèmes9
Asmae MamaneAffiliation unknown4
Mohammed El GhaziUniversité Moulay Ismail de Meknes4
Salah-Eddine DidiSidi Mohamed Ben Abdellah University4
Imane HalkhamsUniversité Privée de Fès4
Dounia DaghoujSidi Mohamed Ben Abdellah University3
Marwa AbdellaouiSidi Mohamed Ben Abdellah University3
Youness BalboulAffiliation unknown3
Ismail AngriInstitut National des Postes et Télécommunications1
Mohammed MahfoudiAffiliation unknown1
Abdellah NajidInstitut National des Postes et Télécommunications1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Resource placement strategy optimization for smart grid application using 5G wireless networks</dc:title><dc:creator>Chafi, Saad-Eddine</dc:creator><dc:creator>Balboul, Younes</dc:creator><dc:creator>Mazer, Said</dc:creator><dc:creator>Fattah, Mohammed</dc:creator><dc:creator>El Bekkali, Moulhime</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;With the evolution of 5G-network, wireless mobile networks are growing to take a strong stand in attempts to achieve ubiquitous large-scale acquisition, connectivity and processing. Smart-grids are among the critical areas that can benefit from the capabilities of the 5G-network, especially internet of things (IoT) applications such as massive machine-type-communications or ultra-reliable low-latency communications. A distributed cloud-services use the cloud, fog and edge computing infrastructures and applications to take advantage of every available resource including network equipment and connected objects to optimize cost, energy, and latency depending on the planned optimization criteria. In this article, we present smart-grid solution based on cloud-services and 5G-network, then we study the integration of smart-grid services in the cloud based on: placement in the cloud and in the end-device, and finally we introduce our proposed solution based on Intelligent placement strategy. The scenarios are evaluated by the iFogSim simulator, and the analyzed results compare the standard cloud placement, edge placement and our intelligent placement with regard to the optimization of the energy consumption, latency, and network usage. The findings show that cloud energy consumption can be substantially reduced using Intelligent Placement while respecting the potential central processing unit (CPU) processing power-limit for each IoT-device used and network constraints in smart-grid.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-08-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i4.pp3932-3942</dc:identifier><dc:identifier>10.11591/ijece.v12i4.pp3932-3942</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 4 (2022); 3932</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/26814/15798</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>