Towards accommodating deadline driven jobs on high performance computing platforms in grid computing environment

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dc.authoridDAKKAK, OMAR/0000-0001-9767-5685
dc.contributor.authorDakkak, Omar
dc.contributor.authorFazea, Yousef
dc.contributor.authorNor, Shahrudin Awang
dc.contributor.authorArif, Suki
dc.date.accessioned2024-09-29T15:57:44Z
dc.date.available2024-09-29T15:57:44Z
dc.date.issued2021
dc.departmentKarabük Üniversitesien_US
dc.description.abstractGrid computing is a connected computing infrastructure that furnishes reliable, stable, ubiquitous, and economic access to high-end computational power. The dynamic nature of the grid brings several challenges to scheduling algorithms that operate in queuing-based scheduling approach. This approach typically performs scheduling based on a certain fixed priority which leads to increase the delay for the running applications. Thus, the overall performance will be deteriorated sharply. The main aim of this study is to minimize the delay in the scheduler for the dynamic jobs. Therefore, this paper tackles dynamic scheduling issues by proposing Swift Gap (SG) mechanism. SG comprises of two stages by applying two mechanisms: A Backfilling Mechanism and Metaheuristic Local Search Optimization Mechanism. In the first stage, the job is placed in the earliest gap available in the local resources' schedules, while the second stage optimizes the performance by checking all available gaps among resources' schedules to find a better gap to place the job in. To further improve the performance, the Completion Time Scheme (CTS) is developed. CTS reduces the delay by placing the job in the gap that guarantees the best start time for the job, and the fastest resource available. The integration between SG and CTS (SG-CTS) is achieved by applying best start time rule in the first stage only, whereas the second stage includes both rules.SGCTS is evaluated through simulation by using real workloads that reflect a real grid system environment. The findings demonstrate that SG-CTS improves the slowdown by 27 %, bounded slowdown by 25 %, tardiness by 21 %, waiting time by 16 % and response time by 7% compared to Conservative backfilling mechanism followed by Gap Search (CONS-GS). Finally, SG-CTS is evaluated against Deadline-Based Backfilling (DBF) algorithm. The evaluation revealed that SG-CTS performs better than DBF for slowdown and waiting time in HPC2N workload.en_US
dc.identifier.doi10.1016/j.jocs.2021.101439
dc.identifier.issn1877-7503
dc.identifier.issn1877-7511
dc.identifier.scopus2-s2.0-85114385224en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.jocs.2021.101439
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4995
dc.identifier.volume54en_US
dc.identifier.wosWOS:000701884900001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal of Computational Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectScheduling jobsen_US
dc.subjectSwift gapen_US
dc.subjectGrid computingen_US
dc.subjectWorkloadsen_US
dc.subjectDeadlinesen_US
dc.subjectHPCen_US
dc.titleTowards accommodating deadline driven jobs on high performance computing platforms in grid computing environmenten_US
dc.typeArticleen_US

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