Kunfu Wang, Yongsheng Hao, Jie Cao*
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1033-1052, 2023, DOI:10.32604/iasc.2023.038036
- 29 April 2023
Abstract Meteorological model tasks require considerable meteorological basis data to support their execution. However, if the task and the meteorological datasets are located on different clouds, that enhances the cost, execution time, and energy consumption of execution meteorological tasks. Therefore, the data layout and task scheduling may work together in the meteorological cloud to avoid being in various locations. To the best of our knowledge, this is the first paper that tries to schedule meteorological tasks with the help of the meteorological data set layout. First, we use the FP-Growth-M (frequent-pattern growth for meteorological model datasets) More >
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