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- W2914772562 abstract "Executing scientific workflows in high-performance cloud computing platforms requires the use of scheduling algorithms that allow workflows execution as fast as possible, while minimizing the monetary cost of such executions. In this work we study how the use of supporting information can offer guidance to scheduling algorithms, helping them to devise more efficient execution plans in terms of the total execution time (makespan) and the total monetary cost. Using two large-scale scientific workflows, our experiments showed that simple modifications on a classical scheduling algorithm (HEFT), in conjunction with the appropriate supporting information, could reduce the monetary cost of an execution in up to 59% and reduce the makespan in up to 8.6%." @default.
- W2914772562 created "2019-02-21" @default.
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- W2914772562 date "2018-07-06" @default.
- W2914772562 modified "2023-09-23" @default.
- W2914772562 title "Assessing the Impact of Supporting Information on the Scheduling of Scientific Workflows on Clouds" @default.
- W2914772562 doi "https://doi.org/10.5753/bresci.2018.3277" @default.
- W2914772562 hasPublicationYear "2018" @default.
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