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Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems

Per-user pricing is possible with cloud computing, a relatively new technology. It provides remote testing and commissioning services through the web, and it utilizes virtualization to make available computing resources. In order to host and store firm data, cloud computing relies on data centers. D...

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Detalles Bibliográficos
Autores principales: Singh, Jyoti, Chen, Jingchao, Singh, Santar Pal, Singh, Mukund Pratap, Hassan, Montaser M., Hassan, Mohamed M., Awal, Halifa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9970718/
https://www.ncbi.nlm.nih.gov/pubmed/36860419
http://dx.doi.org/10.1155/2023/6090282
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author Singh, Jyoti
Chen, Jingchao
Singh, Santar Pal
Singh, Mukund Pratap
Hassan, Montaser M.
Hassan, Mohamed M.
Awal, Halifa
author_facet Singh, Jyoti
Chen, Jingchao
Singh, Santar Pal
Singh, Mukund Pratap
Hassan, Montaser M.
Hassan, Mohamed M.
Awal, Halifa
author_sort Singh, Jyoti
collection PubMed
description Per-user pricing is possible with cloud computing, a relatively new technology. It provides remote testing and commissioning services through the web, and it utilizes virtualization to make available computing resources. In order to host and store firm data, cloud computing relies on data centers. Data centers are made up of networked computers, cables, power supplies, and other components. Cloud data centers have always had to prioritise high performance over energy efficiency. The biggest obstacle is finding a happy medium between system performance and energy consumption, namely, lowering energy use without compromising system performance or service quality. These results were obtained using the PlanetLab dataset. In order to implement the strategy we recommend, it is crucial to get a complete picture of how energy is being consumed in the cloud. Using proper optimization criteria and guided by energy consumption models, this article offers the Capsule Significance Level of Energy Consumption (CSLEC) pattern, which demonstrates how to conserve more energy in cloud data centers. Capsule optimization's prediction phase F1-score of 96.7 percent and 97 percent data accuracy allow for more precise projections of future value.
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spelling pubmed-99707182023-02-28 Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems Singh, Jyoti Chen, Jingchao Singh, Santar Pal Singh, Mukund Pratap Hassan, Montaser M. Hassan, Mohamed M. Awal, Halifa Comput Intell Neurosci Research Article Per-user pricing is possible with cloud computing, a relatively new technology. It provides remote testing and commissioning services through the web, and it utilizes virtualization to make available computing resources. In order to host and store firm data, cloud computing relies on data centers. Data centers are made up of networked computers, cables, power supplies, and other components. Cloud data centers have always had to prioritise high performance over energy efficiency. The biggest obstacle is finding a happy medium between system performance and energy consumption, namely, lowering energy use without compromising system performance or service quality. These results were obtained using the PlanetLab dataset. In order to implement the strategy we recommend, it is crucial to get a complete picture of how energy is being consumed in the cloud. Using proper optimization criteria and guided by energy consumption models, this article offers the Capsule Significance Level of Energy Consumption (CSLEC) pattern, which demonstrates how to conserve more energy in cloud data centers. Capsule optimization's prediction phase F1-score of 96.7 percent and 97 percent data accuracy allow for more precise projections of future value. Hindawi 2023-02-20 /pmc/articles/PMC9970718/ /pubmed/36860419 http://dx.doi.org/10.1155/2023/6090282 Text en Copyright © 2023 Jyoti Singh et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Singh, Jyoti
Chen, Jingchao
Singh, Santar Pal
Singh, Mukund Pratap
Hassan, Montaser M.
Hassan, Mohamed M.
Awal, Halifa
Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title_full Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title_fullStr Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title_full_unstemmed Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title_short Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems
title_sort load-balancing strategy: employing a capsule algorithm for cutting down energy consumption in cloud data centers for next generation wireless systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9970718/
https://www.ncbi.nlm.nih.gov/pubmed/36860419
http://dx.doi.org/10.1155/2023/6090282
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