Israel Institute of Technology
Many scientists perform extensive computations by executing large Bags of similar Tasks (BoTs) in mixtures of computational environments, such as grids and clouds. Although the reliability and cost may vary considerably across these environments, no tool exists to assist scientists in the selection of environments that can both fulfill deadlines and fit budgets. To address this situation, the authors introduce the ExPERT BoT scheduling framework. Their framework systematically selects from a large search space the Pareto-efficient scheduling strategies, that is, the strategies that deliver the best results for both makespan and cost. ExPERT chooses from them the best strategy according to a general, user-specified utility function.