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Checkpointing in selected most fitted resource task scheduling in grid computing

机译:在网格计算中选择的最拟合资源任务调度中的检查点

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Grid applications run on environment that is prone to different kinds of failures. Fault tolerance is the ability to ensure successful delivery of services despite faults that may occur. Our research adds fault tolerance capacity with checkpointing and machine failure, to the current research, Selected Most Fitted (SMF) Task Scheduling for grid computing. This paper simulates one of fault tolerance techniques for grid computing, which is implementing checkpointing into Select Most Fitting Resource for Task Scheduling algorithm (SMF). We applied the algorithm of MeanFailure with Checkpointing in the SMF algorithm and named it MeanFailureCP-SMF. The MeanFailureCP-SMF is simulated using Gridsim with initial checkpointing interval at 20% job execution time. Results show that with MeanFailureCP-SMF has reduce the average execution time (AET) compare to the current SMF and MeanFailure Algorithm.
机译:网格应用程序在易于不同类型的失败的环境中运行。尽管可能发生的故障,容错是确保成功交付服务的能力。我们的研究通过检查点和机器故障增加了容错能力,目前的研究,选择了最适合(SMF)的网格计算任务调度。本文模拟了网格计算的容错技术之一,它正在实现检查点选择任务调度算法(SMF)的最拟合资源。我们使用SMF算法中的检查点应用算法,并将其命名为ItcalfailureCP-SMF。使用GridSim模拟incomfailurecp-SMF,其初始检查点间隔为20%作业执行时间。结果表明,使用含义的平均执行时间(AET)与当前的SMF和含义算法进行比较。

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