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The recent increased use of workflow management systems by large scientific collaborations presents the challenge of scheduling large-scale workflows onto distributed resources. This work aims to partition large-scale scientific workflows in conjunction with resources provisioning to reduce the workflow make span and resource cost.
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Chen et al. (2012) studied this question.
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