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Optimization of Computing Time for Sequential MapReduce Jobs

In order to obtain high cost-effective computing capability and improve resource utilization efficiency, MapReduce clusters are usually shared by multiple jobs, so the scheduling of multiple MapReduce jobs will have an important impact on cluster performance. Aiming at optimizing the average job computing time, this paper studies the scheduling schemes of multiple jobs arriving in Poisson process, and proposes an easy-to-implement median scheduling algorithm. Through simulation experiments, it can be seen that the proposed algorithm can effectively reduce the average computing time of MapReduce jobs.