Cargando…
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...
Autores principales: | , , , , , , |
---|---|
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 |
_version_ | 1784897960075591680 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9970718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT singhjyoti loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT chenjingchao loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT singhsantarpal loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT singhmukundpratap loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT hassanmontaserm loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT hassanmohamedm loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems AT awalhalifa loadbalancingstrategyemployingacapsulealgorithmforcuttingdownenergyconsumptioninclouddatacentersfornextgenerationwirelesssystems |