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Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment
In recent years, we observed the proliferation of cloud data centers (CDCs) and the Internet of Things (IoT). Cloud computing based on CDCs has the drawback of unpredictable response times due to variant delays between service requestors (IoT devices and end devices) and CDCs. This deficiency of clo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926404/ https://www.ncbi.nlm.nih.gov/pubmed/33671542 http://dx.doi.org/10.3390/s21041506 |
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author | Choi, Jonghwa Ahn, Sanghyun |
author_facet | Choi, Jonghwa Ahn, Sanghyun |
author_sort | Choi, Jonghwa |
collection | PubMed |
description | In recent years, we observed the proliferation of cloud data centers (CDCs) and the Internet of Things (IoT). Cloud computing based on CDCs has the drawback of unpredictable response times due to variant delays between service requestors (IoT devices and end devices) and CDCs. This deficiency of cloud computing is especially problematic in providing IoT services with strict timing requirements and as a result, gives birth to fog/edge computing (FEC) whose responsiveness is achieved by placing service images near service requestors. In FEC, the computing nodes located close to service requestors are called fog/edge nodes (FENs). In addition, for an FEN to execute a specific service, it has to be provisioned with the corresponding service image. Most of the previous work on the service provisioning in the FEC environment deals with determining an appropriate FEN satisfying the requirements like delay, CPU and storage from the perspective of one or more service requests. In this paper, we determined how to optimally place service images in consideration of the pre-obtained service demands which may be collected during the prior time interval. The proposed FEC environment is scalable in the sense that the resources of FENs are effectively utilized thanks to the optimal provisioning of services on FENs. We propose two approaches to provision service images on FENs. In order to validate the performance of the proposed mechanisms, intensive simulations were carried out for various service demand scenarios. |
format | Online Article Text |
id | pubmed-7926404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79264042021-03-04 Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment Choi, Jonghwa Ahn, Sanghyun Sensors (Basel) Article In recent years, we observed the proliferation of cloud data centers (CDCs) and the Internet of Things (IoT). Cloud computing based on CDCs has the drawback of unpredictable response times due to variant delays between service requestors (IoT devices and end devices) and CDCs. This deficiency of cloud computing is especially problematic in providing IoT services with strict timing requirements and as a result, gives birth to fog/edge computing (FEC) whose responsiveness is achieved by placing service images near service requestors. In FEC, the computing nodes located close to service requestors are called fog/edge nodes (FENs). In addition, for an FEN to execute a specific service, it has to be provisioned with the corresponding service image. Most of the previous work on the service provisioning in the FEC environment deals with determining an appropriate FEN satisfying the requirements like delay, CPU and storage from the perspective of one or more service requests. In this paper, we determined how to optimally place service images in consideration of the pre-obtained service demands which may be collected during the prior time interval. The proposed FEC environment is scalable in the sense that the resources of FENs are effectively utilized thanks to the optimal provisioning of services on FENs. We propose two approaches to provision service images on FENs. In order to validate the performance of the proposed mechanisms, intensive simulations were carried out for various service demand scenarios. MDPI 2021-02-22 /pmc/articles/PMC7926404/ /pubmed/33671542 http://dx.doi.org/10.3390/s21041506 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Choi, Jonghwa Ahn, Sanghyun Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title | Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title_full | Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title_fullStr | Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title_full_unstemmed | Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title_short | Optimal Service Provisioning for the Scalable Fog/Edge Computing Environment |
title_sort | optimal service provisioning for the scalable fog/edge computing environment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926404/ https://www.ncbi.nlm.nih.gov/pubmed/33671542 http://dx.doi.org/10.3390/s21041506 |
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