A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment
With the increasing of the scale of task or request and dynamic nature of cloud resources, it gives significant issues of load balancing, resource utilization, task allocation, and system performance and so on. To solve those problems many researchers have applied different types of scheduling techn...
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| Format: | Article |
| Language: | English |
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Springer
2022-09-01
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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/S1319157821000033 |
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| author | Arabinda Pradhan Sukant Kishoro Bisoy Amardeep Das |
| author_facet | Arabinda Pradhan Sukant Kishoro Bisoy Amardeep Das |
| author_sort | Arabinda Pradhan |
| collection | DOAJ |
| description | With the increasing of the scale of task or request and dynamic nature of cloud resources, it gives significant issues of load balancing, resource utilization, task allocation, and system performance and so on. To solve those problems many researchers have applied different types of scheduling techniques. But meta-heuristic scheduling is the most accomplish preferred outcomes over conventional heuristics and hybrid scheduling. Among various meta-heuristics algorithms, PSO is a famous metaheuristic technique to solved optimization issue. PSO is appropriate for dynamic task scheduling, workflow scheduling and load balancing. PSO has a strong worldwide searching capability toward the start of the run and a nearby pursuit close to the furthest limit of the run. Therefore, it has been generally utilized in different applications and has made incredible progress. In this paper a systematically reviews is done on different types of particle swarm optimization (PSO) based scheduling strategy with set of challenges and future direction. |
| format | Article |
| id | doaj-art-3cf24ccea2db4a7c86682be80effbec6 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-09-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-3cf24ccea2db4a7c86682be80effbec62025-08-20T03:52:02ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-09-013484888490110.1016/j.jksuci.2021.01.003A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environmentArabinda Pradhan0Sukant Kishoro Bisoy1Amardeep Das2Department of Computer Science and Engineering, C.V. Raman Global University, Bidya Nagar, Mahura, Janla, Bhubaneswar, Odisha 752054, IndiaDepartment of Computer Science and Engineering, C.V. Raman Global University, Bidya Nagar, Mahura, Janla, Bhubaneswar, Odisha 752054, India; Corresponding author.Department of Computer Science and Information Technology, C.V. Raman Global University, Bidya Nagar, Mahura, Janla, Bhubaneswar, Odisha 752054, IndiaWith the increasing of the scale of task or request and dynamic nature of cloud resources, it gives significant issues of load balancing, resource utilization, task allocation, and system performance and so on. To solve those problems many researchers have applied different types of scheduling techniques. But meta-heuristic scheduling is the most accomplish preferred outcomes over conventional heuristics and hybrid scheduling. Among various meta-heuristics algorithms, PSO is a famous metaheuristic technique to solved optimization issue. PSO is appropriate for dynamic task scheduling, workflow scheduling and load balancing. PSO has a strong worldwide searching capability toward the start of the run and a nearby pursuit close to the furthest limit of the run. Therefore, it has been generally utilized in different applications and has made incredible progress. In this paper a systematically reviews is done on different types of particle swarm optimization (PSO) based scheduling strategy with set of challenges and future direction.http://www.sciencedirect.com/science/article/pii/S1319157821000033SchedulingVirtual machineCloud computingMeta-heuristic |
| spellingShingle | Arabinda Pradhan Sukant Kishoro Bisoy Amardeep Das A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment Journal of King Saud University: Computer and Information Sciences Scheduling Virtual machine Cloud computing Meta-heuristic |
| title | A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment |
| title_full | A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment |
| title_fullStr | A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment |
| title_full_unstemmed | A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment |
| title_short | A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment |
| title_sort | survey on pso based meta heuristic scheduling mechanism in cloud computing environment |
| topic | Scheduling Virtual machine Cloud computing Meta-heuristic |
| url | http://www.sciencedirect.com/science/article/pii/S1319157821000033 |
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