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Model-based Simulation And Performance Evaluation Of Grid Scheduling Strategies

机译:基于模型的网格调度策略仿真与性能评估

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Simulation studies of Grid scheduling strategies require representative workloads to produce dependable results. Real production Grid workloads have shown diverse correlation structures and scaling behavior, which are different to the characteristics of the available supercomputer workloads and cannot be captured by Poisson or simple distribution-based models. We present statistical models that are able to reproduce various autocorrelation structures, including pseudo-periodicity and long range dependence. By conducting model-based simulation, we quantitatively evaluate the performance impacts of workload autocorrelations in Grid scheduling. The results indicate that autocorrelations result in system performance degradation, both at the local and the Grid level. It is shown that realistic workload modeling is not only possible, but also necessary to enable dependable Grid scheduling studies.
机译:网格调度策略的仿真研究需要代表性的工作负载才能产生可​​靠的结果。实际的生产Grid工作负载已显示出各种相关结构和扩展行为,这些结构与可用的超级计算机工作负载的特性不同,并且无法被Poisson或基于简单分布的模型捕获。我们提出了能够重现各种自相关结构的统计模型,包括伪周期和远距离依赖性。通过进行基于模型的仿真,我们可以定量评估网格调度中工作负载自相关对性能的影响。结果表明,自相关会导致本地和网格级别的系统性能下降。结果表明,现实的工作负载建模不仅是可行的,而且对于进行可靠的Grid调度研究也是必要的。

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