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An Improved Job Scheduling Algorithm by Utilizing Released Resources for MapReduce

机译:利用MapReduce的发布资源,改进的作业调度算法

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MapReduce has become one standard for big data processing in Cloud computing environment. However job scheduling in this model is always a challenge for the research fraternity and several job scheduling algorithms have already been proposed by researchers addressing various issues. All such algorithms mostly emphasize on meeting of job deadline without taking cognizance of additional released resources being available through intermediate release of resources during processing. In this paper, we propose a new job scheduling algorithm which satisfies job deadline for all scheduled jobs along with utilization of the unused resources so that more number of jobs can be scheduled and the overall system efficiency will be increased.
机译:MapReduce已成为云计算环境中的大数据处理的一个标准。然而,该模型中的作业调度始终是研究兄弟会的挑战,研究人员已经提出了几个工作调度算法,解决了各种问题。所有此类算法大多都强调了就业截止日期会议,而不考虑通过在处理期间通过中间发布资源提供额外的释放资源。在本文中,我们提出了一种新的作业调度算法,其满足所有调度作业的作业截止日期以及利用未使用的资源,以便可以调度更多数量的作业,并且将增加整体系统效率。

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