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The advent of cloud computing makes scientists to extend their research environments over supercomputers to on-demand and dynamically scalable resources. Science cloud becomes a trend in various scientific domains these days. However, it is difficult to provide optimal job execution environment rapidly and dynamically depending on user's demands. Therefore, it is very important to predict user's requirements...
Grids have ensured to solve a large-scale complex scientific problem with utilizing many heterogeneous resources that are geographically separated. However, as grid resources and scientific applications become diverse, the difficulty of their execution management and control has been increased. In this paper, we propose JARS (Job history-based Adaptive grid Resource Selection) system and evaluate...
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