Usage Patterns to Provision for Scientific Experimentation in Clouds
Usage Patterns to Provision for Scientific Experimentation in Clouds
复制标题
云中科学实验的使用模式
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Beth Plale
中科院分区：
文献类型：
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作者：
E. C. Withana;Beth Plale
在需要按需提供资源的驱动下，科学家正在转向商业和研究测试床云计算资源来运行其科学实验。与早期平台不同，在云计算资源上的作业调度是吞吐量和执行成本之间的平衡。在这种情况下，我们认为使用模式可以改善工作执行，因为这些模式允许系统计划，舞台和优化调度决策。本文介绍了一种新的方法，用于利用从基于知识的技术中汲取的用户模式，以改善云计算环境中一系列主动工作流程和作业的执行。使用经验分析，我们为两个不同的工作负载建立了预测方法的准确性，并演示了如何使用这些知识来改善工作执行。
Driven by the need to provision resources on demand, scientists are turning to commercial and research test-bed Cloud computing resources to run their scientific experiments. Job scheduling on cloud computing resources, unlike earlier platforms, is a balance between throughput and cost of executions. Within this context, we posit that usage patterns can improve the job execution, because these patterns allow a system to plan, stage and optimize scheduling decisions. This paper introduces a novel approach to utilization of user patterns drawn from knowledge-based techniques, to improve execution across a series of active workflows and jobs in cloud computing environments. Using empirical analysis we establish the accuracy of our prediction approach for two different workloads and demonstrate how this knowledge can be used to improve job executions.