ROA-CONS: Raccoon Optimization for 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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Bibliographic Details
Published in:Symmetry (Basel) 2021-12, Vol.13 (12), p.2270
Main Authors: Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan
Format: Article
Language:English
Subjects:
Algorithms
Business machines
Computers
conservative backfilling
Efficiency
Employment
Heterogeneity
Heuristic
Hybridization
job scheduling
Methods
Optimization
parallel computer
Personal computers
Planning
raccoon optimization algorithm
Response time
Schedules
Scheduling
User satisfaction
Workstations
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Summary: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.
ISSN:2073-8994
2073-8994
DOI:10.3390/sym13122270