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An Evaluation of Optimizing for FUD in Scheduling for Shared Computing Environments

机译:共享计算环境调度中的FUD优化评估

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Scheduling systems for shared computing environments such as Cloud, Grid and Cluster computing act as the intermediator agent between the participating users with their requests in form of jobs or tasks, and the resources being shared. We will look at nine scheduling systems in this paper, and evaluate how each would be measured against the three optimizing parameters of Fairness, Utilization and Dynamicity (FUD). The variables are independent to each other, but design decisions made to optimize one variable affects the other two variables. We will demonstrate that batch job-based scheduling systems tend to focus on utilization as the means to reduce response time, whereas interactive task-based scheduling systems tend to focus more on dynamicity as the means to deal with rapid changes in the environment.
机译:用于共享计算环境(如云,网格和群集计算)的调度系统充当参与用户之间的中介代理,这些用户以作业或任务的形式提出其请求,并共享资源。我们将研究本文中的9个调度系统,并评估如何根据公平性,利用率和动态性(FUD)的三个优化参数来测量每个系统。变量彼此独立,但是为优化一个变量而做出的设计决策会影响其他两个变量。我们将证明,基于批处理作业的调度系统倾向于将注意力集中在利用上,以减少响应时间,而基于交互式任务的调度系统则倾向于把重点放在动态上,以应对环境的快速变化。

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