Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers
Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources. Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world. However, cloud data centers consume vas...
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/61719/ http://psasir.upm.edu.my/id/eprint/61719/1/Energy-efficient%20algorithms%20for%20dynamic%20virtual%20machine.pdf |
| _version_ | 1848854473375481856 |
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| author | Khoshkholghi, Mohammad Ali Derahman, Mohd Noor Abdullah, Azizol Subramaniam, Shamala Othman, Mohamed |
| author_facet | Khoshkholghi, Mohammad Ali Derahman, Mohd Noor Abdullah, Azizol Subramaniam, Shamala Othman, Mohamed |
| author_sort | Khoshkholghi, Mohammad Ali |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources. Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world. However, cloud data centers consume vast amounts of electrical energy, contributing to high-operational costs, and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and putting idle nodes in sleep mode allows cloud providers to optimize resource utilization and reduce energy consumption. However, aggressive VM consolidation may degrade the performance. Therefore, an energy-performance tradeoff between providing high-quality service to customers and reducing power consumption is desired. In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers. The aim is to improve the utilization of computing resources and reduce energy consumption under SLA constraints regarding CPU, RAM, and bandwidth. The efficiency of the proposed algorithms is validated by conducting extensive simulations. The results of the evaluation clearly show that the proposed algorithms significantly reduce energy consumption while providing a high level of commitment to the SLA. Based on the proposed algorithms, energy consumption can be reduced |
| first_indexed | 2025-11-15T11:10:25Z |
| format | Article |
| id | upm-61719 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:10:25Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-617192019-01-10T03:04:44Z http://psasir.upm.edu.my/id/eprint/61719/ Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers Khoshkholghi, Mohammad Ali Derahman, Mohd Noor Abdullah, Azizol Subramaniam, Shamala Othman, Mohamed Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources. Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world. However, cloud data centers consume vast amounts of electrical energy, contributing to high-operational costs, and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and putting idle nodes in sleep mode allows cloud providers to optimize resource utilization and reduce energy consumption. However, aggressive VM consolidation may degrade the performance. Therefore, an energy-performance tradeoff between providing high-quality service to customers and reducing power consumption is desired. In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers. The aim is to improve the utilization of computing resources and reduce energy consumption under SLA constraints regarding CPU, RAM, and bandwidth. The efficiency of the proposed algorithms is validated by conducting extensive simulations. The results of the evaluation clearly show that the proposed algorithms significantly reduce energy consumption while providing a high level of commitment to the SLA. Based on the proposed algorithms, energy consumption can be reduced Institute of Electrical and Electronics Engineers 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61719/1/Energy-efficient%20algorithms%20for%20dynamic%20virtual%20machine.pdf Khoshkholghi, Mohammad Ali and Derahman, Mohd Noor and Abdullah, Azizol and Subramaniam, Shamala and Othman, Mohamed (2017) Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers. IEEE Access, 5. 10709 -10722. ISSN 2169-3536 https://ieeexplore.ieee.org/document/7937801 10.1109/ACCESS.2017.2711043 |
| spellingShingle | Khoshkholghi, Mohammad Ali Derahman, Mohd Noor Abdullah, Azizol Subramaniam, Shamala Othman, Mohamed Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title | Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title_full | Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title_fullStr | Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title_full_unstemmed | Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title_short | Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| title_sort | energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers |
| url | http://psasir.upm.edu.my/id/eprint/61719/ http://psasir.upm.edu.my/id/eprint/61719/ http://psasir.upm.edu.my/id/eprint/61719/ http://psasir.upm.edu.my/id/eprint/61719/1/Energy-efficient%20algorithms%20for%20dynamic%20virtual%20machine.pdf |