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Towards an Effective Service Allocation in Fog Computing

The Internet of Things (IoT) generates a large volume of data whenever devices are interconnected and exchange data across a network. Consequently, a variety of services with diverse needs arises, including capacity requirements, data quality, and latency demands. These services operate on fog compu...

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Detalles Bibliográficos
Autores principales: Alsemmeari, Rayan A., Dahab, Mohamed Yehia, Alturki, Badraddin, Alsulami, Abdulaziz A., Alsini, Raed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490245/
https://www.ncbi.nlm.nih.gov/pubmed/37687784
http://dx.doi.org/10.3390/s23177327
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author Alsemmeari, Rayan A.
Dahab, Mohamed Yehia
Alturki, Badraddin
Alsulami, Abdulaziz A.
Alsini, Raed
author_facet Alsemmeari, Rayan A.
Dahab, Mohamed Yehia
Alturki, Badraddin
Alsulami, Abdulaziz A.
Alsini, Raed
author_sort Alsemmeari, Rayan A.
collection PubMed
description The Internet of Things (IoT) generates a large volume of data whenever devices are interconnected and exchange data across a network. Consequently, a variety of services with diverse needs arises, including capacity requirements, data quality, and latency demands. These services operate on fog computing devices, which are limited in power and bandwidth compared to the cloud. The primary challenge lies in determining the optimal location for service implementation: in the fog, in the cloud, or in a hybrid setup. This paper introduces an efficient allocation technique that moves processing closer to the network’s fog side. It explores the optimal allocation of devices and services while maintaining resource utilization within an IoT architecture. The paper also examines the significance of allocating services to devices and optimizing resource utilization in fog computing. In IoT scenarios, where a wide range of services and devices coexist, it becomes crucial to effectively assign services to devices. We propose priority-based service allocation (PSA) and sort-based service allocation (SSA) techniques, which are employed to determine the optimal order for the utilizing devices to perform different services. Experimental results demonstrate that our proposed technique reduces data communication over the network by 88%, which is achieved by allocating most services locally in the fog. We increased the distribution of services to fog devices by 96%, while simultaneously minimizing the wastage of fog resources.
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spelling pubmed-104902452023-09-09 Towards an Effective Service Allocation in Fog Computing Alsemmeari, Rayan A. Dahab, Mohamed Yehia Alturki, Badraddin Alsulami, Abdulaziz A. Alsini, Raed Sensors (Basel) Article The Internet of Things (IoT) generates a large volume of data whenever devices are interconnected and exchange data across a network. Consequently, a variety of services with diverse needs arises, including capacity requirements, data quality, and latency demands. These services operate on fog computing devices, which are limited in power and bandwidth compared to the cloud. The primary challenge lies in determining the optimal location for service implementation: in the fog, in the cloud, or in a hybrid setup. This paper introduces an efficient allocation technique that moves processing closer to the network’s fog side. It explores the optimal allocation of devices and services while maintaining resource utilization within an IoT architecture. The paper also examines the significance of allocating services to devices and optimizing resource utilization in fog computing. In IoT scenarios, where a wide range of services and devices coexist, it becomes crucial to effectively assign services to devices. We propose priority-based service allocation (PSA) and sort-based service allocation (SSA) techniques, which are employed to determine the optimal order for the utilizing devices to perform different services. Experimental results demonstrate that our proposed technique reduces data communication over the network by 88%, which is achieved by allocating most services locally in the fog. We increased the distribution of services to fog devices by 96%, while simultaneously minimizing the wastage of fog resources. MDPI 2023-08-22 /pmc/articles/PMC10490245/ /pubmed/37687784 http://dx.doi.org/10.3390/s23177327 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alsemmeari, Rayan A.
Dahab, Mohamed Yehia
Alturki, Badraddin
Alsulami, Abdulaziz A.
Alsini, Raed
Towards an Effective Service Allocation in Fog Computing
title Towards an Effective Service Allocation in Fog Computing
title_full Towards an Effective Service Allocation in Fog Computing
title_fullStr Towards an Effective Service Allocation in Fog Computing
title_full_unstemmed Towards an Effective Service Allocation in Fog Computing
title_short Towards an Effective Service Allocation in Fog Computing
title_sort towards an effective service allocation in fog computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490245/
https://www.ncbi.nlm.nih.gov/pubmed/37687784
http://dx.doi.org/10.3390/s23177327
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