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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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Main Authors: Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan
Format: Article
Published: MDPI AG 2021
Online Access:http://psasir.upm.edu.my/id/eprint/94983/
https://www.mdpi.com/2073-8994/13/12/2270
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spelling my.upm.eprints.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
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
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.
format Article
author Koohi, Sina Zangbari
Abdul Hamid, Nor Asilah Wati
Othman, Mohamed
Ibragimov, Gafurjan
spellingShingle Koohi, Sina Zangbari
Abdul Hamid, Nor Asilah Wati
Othman, Mohamed
Ibragimov, Gafurjan
ROA-CONS: raccoon optimization job scheduling
author_facet Koohi, Sina Zangbari
Abdul Hamid, Nor Asilah Wati
Othman, Mohamed
Ibragimov, Gafurjan
author_sort Koohi, Sina Zangbari
title ROA-CONS: raccoon optimization job scheduling
title_short 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_sort roa-cons: raccoon optimization job scheduling
publisher MDPI AG
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/94983/
https://www.mdpi.com/2073-8994/13/12/2270
_version_ 1758579837178478592
score 13.211869

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