Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment
Load balancing among virtual machines (VMs) is significant for delivering the cloud services in optimized way with minimum cost paid and total time acquired to deliver the services. In this paper, the various research gaps for load balancing optimization in the past literature have been presented, w...
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| Format: | Article |
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Springer
2022-03-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157818309820 |
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| author | Amanpreet Kaur Bikrampal Kaur |
| author_facet | Amanpreet Kaur Bikrampal Kaur |
| author_sort | Amanpreet Kaur |
| collection | DOAJ |
| description | Load balancing among virtual machines (VMs) is significant for delivering the cloud services in optimized way with minimum cost paid and total time acquired to deliver the services. In this paper, the various research gaps for load balancing optimization in the past literature have been presented, which need to be addressed for solving the load balancing problem in cloud environment. In present work, Hybrid approach based resource provisioning and load balancing framework for workflows execution has been proposed to optimize the utilization of VMs with uniform load distribution. The proposed framework is based on the hybridization of heuristic techniques with metaheuristic algorithm to achieve its optimal performance in terms of makespan and cost. Two hybrid approaches have been proposed for HDD-PLB framework-Hybrid Predict Earliest Finish Time (PEFT) Heuristic with Ant Colony Optimization (ACO) metaheuristic (HPA) and Hybrid Heterogeneous Earliest Finish Time (HEFT) heuristic with ACO (HHA). The two proposed approaches for load balancing have been analyzed and compared to determine which is superior for proposed HDD-PLB framework. |
| format | Article |
| id | doaj-art-751e6fabf1044e3cb166ec0a8dd5e7d7 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-751e6fabf1044e3cb166ec0a8dd5e7d72025-08-20T03:52:03ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-03-0134381382410.1016/j.jksuci.2019.02.010Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environmentAmanpreet Kaur0Bikrampal Kaur1Research Scholar, IKGPTU, Kapurthala, India; Chandigarh Engineering College, Landran, India; Corresponding author.Chandigarh Engineering College, Landran, Mohali, Punjab, IndiaLoad balancing among virtual machines (VMs) is significant for delivering the cloud services in optimized way with minimum cost paid and total time acquired to deliver the services. In this paper, the various research gaps for load balancing optimization in the past literature have been presented, which need to be addressed for solving the load balancing problem in cloud environment. In present work, Hybrid approach based resource provisioning and load balancing framework for workflows execution has been proposed to optimize the utilization of VMs with uniform load distribution. The proposed framework is based on the hybridization of heuristic techniques with metaheuristic algorithm to achieve its optimal performance in terms of makespan and cost. Two hybrid approaches have been proposed for HDD-PLB framework-Hybrid Predict Earliest Finish Time (PEFT) Heuristic with Ant Colony Optimization (ACO) metaheuristic (HPA) and Hybrid Heterogeneous Earliest Finish Time (HEFT) heuristic with ACO (HHA). The two proposed approaches for load balancing have been analyzed and compared to determine which is superior for proposed HDD-PLB framework.http://www.sciencedirect.com/science/article/pii/S1319157818309820Virtual machines (VMs)WorkflowsHEFTPEFTACOOptimization |
| spellingShingle | Amanpreet Kaur Bikrampal Kaur Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment Journal of King Saud University: Computer and Information Sciences Virtual machines (VMs) Workflows HEFT PEFT ACO Optimization |
| title | Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment |
| title_full | Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment |
| title_fullStr | Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment |
| title_full_unstemmed | Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment |
| title_short | Load balancing optimization based on hybrid Heuristic-Metaheuristic techniques in cloud environment |
| title_sort | load balancing optimization based on hybrid heuristic metaheuristic techniques in cloud environment |
| topic | Virtual machines (VMs) Workflows HEFT PEFT ACO Optimization |
| url | http://www.sciencedirect.com/science/article/pii/S1319157818309820 |
| work_keys_str_mv | AT amanpreetkaur loadbalancingoptimizationbasedonhybridheuristicmetaheuristictechniquesincloudenvironment AT bikrampalkaur loadbalancingoptimizationbasedonhybridheuristicmetaheuristictechniquesincloudenvironment |