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In this study, based on the consideration of energy consumption, we take to improve the strategy of the MapReduce job scheduling algorithm, in order to reduce the average response time for task scheduling of interactive jobs in the network. In accordance with the job priority grouping to adjust the scheduling task response time which can reduce the impact of network congestion, with good results that increase the throughput of the system transferring data and computing power.

Based on the MapReduce Model for Data-intensive Computing of Energy Scheduling Algorithm Strategy