SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds
Cloud computing emerged as one of the leading computational paradigms due to elastic resource provisioning and pay-as-you-go model. Large data centers are used by the service providers to host the various services. These data centers consume enormous energy, which leads to increase in operating cost...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8835038/ |
| _version_ | 1818596585744891904 |
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| author | Saad Mustafa Kinza Sattar Junaid Shuja Shahzad Sarwar Tahir Maqsood Sajjad A. Madani Sghaier Guizani |
| author_facet | Saad Mustafa Kinza Sattar Junaid Shuja Shahzad Sarwar Tahir Maqsood Sajjad A. Madani Sghaier Guizani |
| author_sort | Saad Mustafa |
| collection | DOAJ |
| description | Cloud computing emerged as one of the leading computational paradigms due to elastic resource provisioning and pay-as-you-go model. Large data centers are used by the service providers to host the various services. These data centers consume enormous energy, which leads to increase in operating costs and carbon footprints. Therefore, green cloud computing is a necessity, which not only reduces energy consumption, but also affects the environment positively. In order to reduce the energy consumption, workload consolidation approach is used that consolidates the tasks in minimum possible servers. However, workload consolidation may lead to service level agreement (SLA) violations due to non-availability of resources on the server. Therefore, workload consolidation techniques should consider the aforementioned problem. In this paper, we present two consolidation based energy-efficient techniques that reduce energy consumption along with resultant SLA violations. In addition to that, we also enhanced the existing Enhanced-Conscious Task Consolidation (ECTC) and Maximum Utilization (MaxUtil) techniques that attempt to reduce energy consumption and SLA violations. Experimental results show that the proposed techniques perform better than the selected heuristic based techniques in terms of energy, SLA, and migrations. |
| first_indexed | 2024-12-16T11:34:15Z |
| format | Article |
| id | doaj.art-fec3b4bd7364449ba607fbff4cdaecb3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T11:34:15Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-fec3b4bd7364449ba607fbff4cdaecb32022-12-21T22:33:09ZengIEEEIEEE Access2169-35362019-01-01713525613526710.1109/ACCESS.2019.29411458835038SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in CloudsSaad Mustafa0https://orcid.org/0000-0002-1443-7890Kinza Sattar1Junaid Shuja2https://orcid.org/0000-0003-0726-5311Shahzad Sarwar3Tahir Maqsood4Sajjad A. Madani5Sghaier Guizani6Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, PakistanKnowledge Unit of Science and Technology, University of Management and Technology, Sialkot Campus, Sialkot, PakistanDepartment of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, PakistanPunjab University College of Information Technology, University of Punjab, Lahore, PakistanDepartment of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, PakistanCOMSATS University Islamabad, Wah Campus, Wah, PakistanCollege of Engineering, Alfaisal University, Riyadh, Saudi ArabiaCloud computing emerged as one of the leading computational paradigms due to elastic resource provisioning and pay-as-you-go model. Large data centers are used by the service providers to host the various services. These data centers consume enormous energy, which leads to increase in operating costs and carbon footprints. Therefore, green cloud computing is a necessity, which not only reduces energy consumption, but also affects the environment positively. In order to reduce the energy consumption, workload consolidation approach is used that consolidates the tasks in minimum possible servers. However, workload consolidation may lead to service level agreement (SLA) violations due to non-availability of resources on the server. Therefore, workload consolidation techniques should consider the aforementioned problem. In this paper, we present two consolidation based energy-efficient techniques that reduce energy consumption along with resultant SLA violations. In addition to that, we also enhanced the existing Enhanced-Conscious Task Consolidation (ECTC) and Maximum Utilization (MaxUtil) techniques that attempt to reduce energy consumption and SLA violations. Experimental results show that the proposed techniques perform better than the selected heuristic based techniques in terms of energy, SLA, and migrations.https://ieeexplore.ieee.org/document/8835038/Energy efficiencyworkload consolidationSLA violationresource managementcloud computing |
| spellingShingle | Saad Mustafa Kinza Sattar Junaid Shuja Shahzad Sarwar Tahir Maqsood Sajjad A. Madani Sghaier Guizani SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds IEEE Access Energy efficiency workload consolidation SLA violation resource management cloud computing |
| title | SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds |
| title_full | SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds |
| title_fullStr | SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds |
| title_full_unstemmed | SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds |
| title_short | SLA-Aware Best Fit Decreasing Techniques for Workload Consolidation in Clouds |
| title_sort | sla aware best fit decreasing techniques for workload consolidation in clouds |
| topic | Energy efficiency workload consolidation SLA violation resource management cloud computing |
| url | https://ieeexplore.ieee.org/document/8835038/ |
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