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Energy efficient service placement in fog computing

The Internet of Things (IoT) concept evolved into a slew of applications. To satisfy the requests of these applications, using cloud computing is troublesome because of the high latency caused by the distance between IoT devices and cloud resources. Fog computing has become promising with its geogra...

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Detalles Bibliográficos
Autores principales: Vadde, Usha, Kompalli, Vijaya Sri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455019/
https://www.ncbi.nlm.nih.gov/pubmed/36092002
http://dx.doi.org/10.7717/peerj-cs.1035
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author Vadde, Usha
Kompalli, Vijaya Sri
author_facet Vadde, Usha
Kompalli, Vijaya Sri
author_sort Vadde, Usha
collection PubMed
description The Internet of Things (IoT) concept evolved into a slew of applications. To satisfy the requests of these applications, using cloud computing is troublesome because of the high latency caused by the distance between IoT devices and cloud resources. Fog computing has become promising with its geographically distributed infrastructure for providing resources using fog nodes near IoT devices, thereby reducing the bandwidth and latency. A geographical distribution, heterogeneity and resource constraints of fog nodes introduce the key challenge of placing application modules/services in such a large scale infrastructure. In this work, we propose an improved version of the JAYA approach for optimal placement of modules that minimizes the energy consumption of a fog landscape. We analyzed the performance in terms of energy consumption, network usage, delays and execution time. Using iFogSim, we ran simulations and observed that our approach reduces on average 31% of the energy consumption compared to modern methods.
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spelling pubmed-94550192022-09-09 Energy efficient service placement in fog computing Vadde, Usha Kompalli, Vijaya Sri PeerJ Comput Sci Adaptive and Self-Organizing Systems The Internet of Things (IoT) concept evolved into a slew of applications. To satisfy the requests of these applications, using cloud computing is troublesome because of the high latency caused by the distance between IoT devices and cloud resources. Fog computing has become promising with its geographically distributed infrastructure for providing resources using fog nodes near IoT devices, thereby reducing the bandwidth and latency. A geographical distribution, heterogeneity and resource constraints of fog nodes introduce the key challenge of placing application modules/services in such a large scale infrastructure. In this work, we propose an improved version of the JAYA approach for optimal placement of modules that minimizes the energy consumption of a fog landscape. We analyzed the performance in terms of energy consumption, network usage, delays and execution time. Using iFogSim, we ran simulations and observed that our approach reduces on average 31% of the energy consumption compared to modern methods. PeerJ Inc. 2022-07-19 /pmc/articles/PMC9455019/ /pubmed/36092002 http://dx.doi.org/10.7717/peerj-cs.1035 Text en ©2022 Vadde and Kompalli https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Adaptive and Self-Organizing Systems
Vadde, Usha
Kompalli, Vijaya Sri
Energy efficient service placement in fog computing
title Energy efficient service placement in fog computing
title_full Energy efficient service placement in fog computing
title_fullStr Energy efficient service placement in fog computing
title_full_unstemmed Energy efficient service placement in fog computing
title_short Energy efficient service placement in fog computing
title_sort energy efficient service placement in fog computing
topic Adaptive and Self-Organizing Systems
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455019/
https://www.ncbi.nlm.nih.gov/pubmed/36092002
http://dx.doi.org/10.7717/peerj-cs.1035
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