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Improved FIFO Scheduling Algorithm Based on Fuzzy Clustering in Cloud Computing

机译:云计算中基于模糊聚类的改进FIFO调度算法

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In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks’ waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. We construct a task model, resource model, and analyze tasks’ preference, then classify resources with fuzzy clustering algorithms. Based on the parameters of cloud tasks, the algorithm will calculate resource expectation and assign tasks to different resource clusters, so the complexity of resource selection will be decreased. As a result, the algorithm will reduce tasks’ waiting time and improve the resource utilization. The experiment results show that the proposed algorithm shortens the execution time of tasks and increases the resource utilization.
机译:在云计算中,基于先进先出(FIFO)调度算法,一些大任务可能会占用太多资源,而一些小任务可能会等待很长时间。为了减少任务的等待时间,我们提出了一种基于模糊聚类算法的任务调度算法。我们构建任务模型,资源模型,并分析任务的偏好,然后使用模糊聚类算法对资源进行分类。基于云任务的参数,该算法将计算资源期望值并将任务分配给不同的资源集群,从而降低资源选择的复杂性。结果,该算法将减少任务的等待时间并提高资源利用率。实验结果表明,该算法缩短了任务执行时间,提高了资源利用率。

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