A mathematical programming approach for resource allocation of data analysis workflows on heterogeneous clusters

نویسندگان

چکیده

Abstract Scientific communities are motivated to schedule their large-scale data analysis workflows in heterogeneous cluster environments because of privacy and financial issues. In such containing considerably diverse resources, efficient resource allocation approaches essential for reaching high performance. Accordingly, this research addresses the scheduling problem with bag-of-task form minimize total runtime (makespan). To aim, we develop a mixed-integer linear programming model (MILP). The proposed contains binary decision variables determining which tasks should be assigned nodes. Also, it constraints fulfill requirements as memory policy. Comparative results show that our approach outperforms related most cases. As part post-optimality analysis, some secondary preferences imposed on obtain preferred optimal solution. We analyze relaxation makespan hope significantly reducing number consumed

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ژورنال

عنوان ژورنال: The Journal of Supercomputing

سال: 2023

ISSN: ['0920-8542', '1573-0484']

DOI: https://doi.org/10.1007/s11227-023-05325-w