ROA-CONS: raccoon optimization job scheduling
High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on the...
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| Format: | Article |
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MDPI AG
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/94983/ |
| _version_ | 1848862044862808064 |
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| author | Koohi, Sina Zangbari Abdul Hamid, Nor Asilah Wati Othman, Mohamed Ibragimov, Gafurjan |
| author_facet | Koohi, Sina Zangbari Abdul Hamid, Nor Asilah Wati Othman, Mohamed Ibragimov, Gafurjan |
| author_sort | Koohi, Sina Zangbari |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on their performance. HPC’s job scheduling is intended to develop an operational strategy which utilises resources efficiently and avoids delays. An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. Another problem for parallel job scheduling is user fairness. One of the issues in this field of study is providing a balanced schedule that enhances efficiency and user fairness. ROA-CONS is a new job scheduling method proposed in this paper. It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. It contributes to the development of a symmetrical schedule that increases user satisfaction and performance. In comparison with other well-known job scheduling algorithms, the simulation assesses the effectiveness of the proposed method. The results demonstrate that the proposed strategy offers improved schedules that reduce the overall system’s job waiting and response times. |
| first_indexed | 2025-11-15T13:10:46Z |
| format | Article |
| id | upm-94983 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:10:46Z |
| publishDate | 2021 |
| publisher | MDPI AG |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-949832023-02-10T03:21:12Z http://psasir.upm.edu.my/id/eprint/94983/ ROA-CONS: raccoon optimization job scheduling Koohi, Sina Zangbari Abdul Hamid, Nor Asilah Wati Othman, Mohamed Ibragimov, Gafurjan High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on their performance. HPC’s job scheduling is intended to develop an operational strategy which utilises resources efficiently and avoids delays. An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. Another problem for parallel job scheduling is user fairness. One of the issues in this field of study is providing a balanced schedule that enhances efficiency and user fairness. ROA-CONS is a new job scheduling method proposed in this paper. It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. It contributes to the development of a symmetrical schedule that increases user satisfaction and performance. In comparison with other well-known job scheduling algorithms, the simulation assesses the effectiveness of the proposed method. The results demonstrate that the proposed strategy offers improved schedules that reduce the overall system’s job waiting and response times. MDPI AG 2021-11-29 Article PeerReviewed Koohi, Sina Zangbari and Abdul Hamid, Nor Asilah Wati and Othman, Mohamed and Ibragimov, Gafurjan (2021) ROA-CONS: raccoon optimization job scheduling. Symmetry, 13 (12). art. no. 2270. pp. 1-16. ISSN 2073-8994 https://www.mdpi.com/2073-8994/13/12/2270 10.3390/sym13122270 |
| spellingShingle | Koohi, Sina Zangbari Abdul Hamid, Nor Asilah Wati Othman, Mohamed Ibragimov, Gafurjan ROA-CONS: raccoon optimization job scheduling |
| title | ROA-CONS: raccoon optimization job scheduling |
| title_full | ROA-CONS: raccoon optimization job scheduling |
| title_fullStr | ROA-CONS: raccoon optimization job scheduling |
| title_full_unstemmed | ROA-CONS: raccoon optimization job scheduling |
| title_short | ROA-CONS: raccoon optimization job scheduling |
| title_sort | roa-cons: raccoon optimization job scheduling |
| url | http://psasir.upm.edu.my/id/eprint/94983/ http://psasir.upm.edu.my/id/eprint/94983/ http://psasir.upm.edu.my/id/eprint/94983/ |