A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources
Numerous green computing applications employ sustainable energy sources to abate redundant energy consumption. Renewable energy sources are vital to improving energy efficiency and should be used optimally. This paper introduces the Energy Proficient Computing Framework (EPCF) in the resource-centri...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10314521/ |
| _version_ | 1827755126176088064 |
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| author | Ghulam Abbas Mohammed Hatatah Aamir Ali Ezzeddine Touti Ahmed Alshahir Ali M. Elrashidi |
| author_facet | Ghulam Abbas Mohammed Hatatah Aamir Ali Ezzeddine Touti Ahmed Alshahir Ali M. Elrashidi |
| author_sort | Ghulam Abbas |
| collection | DOAJ |
| description | Numerous green computing applications employ sustainable energy sources to abate redundant energy consumption. Renewable energy sources are vital to improving energy efficiency and should be used optimally. This paper introduces the Energy Proficient Computing Framework (EPCF) in the resource-centric cloud environment. The main objective of the EPCF is to improve the shared efficiency of energy distribution in the computing systems. Renewable energy is distributed among computers according to their running status and the number of calculations available. Traditional k-means clustering separates the states and computations when making this determination. This mapping procedure is repeated throughout the computation until the energy is dispersed without waste. Energy is conserved for the later use if the sources of the leak can be located in advance. As a result, we can conserve and use energy more effectively. In addition, it speeds up calculations and decreases service allocation waiting times. The proposed framework achieves 14.69% less energy cost for the different service al-location rates, 6.34% less energy drain, and 14.4% high efficiency. |
| first_indexed | 2024-03-11T07:58:51Z |
| format | Article |
| id | doaj.art-7fbcb92a8b7148f88a2da527c12ff3a6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T07:58:51Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7fbcb92a8b7148f88a2da527c12ff3a62023-11-17T00:01:02ZengIEEEIEEE Access2169-35362023-01-011112654212655410.1109/ACCESS.2023.333198710314521A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy SourcesGhulam Abbas0https://orcid.org/0000-0001-7383-6798Mohammed Hatatah1Aamir Ali2https://orcid.org/0000-0002-1574-9060Ezzeddine Touti3Ahmed Alshahir4https://orcid.org/0000-0003-3804-4925Ali M. Elrashidi5School of Electrical Engineering, Southeast University, Nanjing, ChinaDepartment of Electrical Engineering, Al-Baha University, Alaqiq, Saudi ArabiaDepartment of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, PakistanDepartment of Electrical Engineering, College of Engineering, Northern Border University, Arar, Saudi ArabiaDepartment of Electrical Engineering, College of Engineering, Jouf University, Sakakah, Saudi ArabiaDepartment of Electrical Engineering, University of Business and Technology, Jeddah, Saudi ArabiaNumerous green computing applications employ sustainable energy sources to abate redundant energy consumption. Renewable energy sources are vital to improving energy efficiency and should be used optimally. This paper introduces the Energy Proficient Computing Framework (EPCF) in the resource-centric cloud environment. The main objective of the EPCF is to improve the shared efficiency of energy distribution in the computing systems. Renewable energy is distributed among computers according to their running status and the number of calculations available. Traditional k-means clustering separates the states and computations when making this determination. This mapping procedure is repeated throughout the computation until the energy is dispersed without waste. Energy is conserved for the later use if the sources of the leak can be located in advance. As a result, we can conserve and use energy more effectively. In addition, it speeds up calculations and decreases service allocation waiting times. The proposed framework achieves 14.69% less energy cost for the different service al-location rates, 6.34% less energy drain, and 14.4% high efficiency.https://ieeexplore.ieee.org/document/10314521/Renewable energyenergy allocationgreen computingk-means clusteringsustainable energy |
| spellingShingle | Ghulam Abbas Mohammed Hatatah Aamir Ali Ezzeddine Touti Ahmed Alshahir Ali M. Elrashidi A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources IEEE Access Renewable energy energy allocation green computing k-means clustering sustainable energy |
| title | A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources |
| title_full | A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources |
| title_fullStr | A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources |
| title_full_unstemmed | A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources |
| title_short | A Novel Energy Proficient Computing Framework for Green Computing Using Sustainable Energy Sources |
| title_sort | novel energy proficient computing framework for green computing using sustainable energy sources |
| topic | Renewable energy energy allocation green computing k-means clustering sustainable energy |
| url | https://ieeexplore.ieee.org/document/10314521/ |
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