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Response Surface Modelling for Performance Analysis of Scientific Workflow Application in Cloud
Cluster Computing ( IF 3.6 ) Pub Date : 2020-09-09 , DOI: 10.1007/s10586-020-03180-5
Prathibha Soma , B. Latha

Scientific workflow applications are used by scientists to carry out research in various domains such as Physics, Chemistry, Astronomy etc. These applications require huge computational resources and currently cloud platform is used for efficiently running these applications. To improve the makespan and cost in workflow execution in cloud platform it requires to identify proper number of Virtual Machines (VM) and choose proper VM type. As cloud platform is dynamic, the available resources and the type of the resources are the two important factors on the cost and makespan of workflow execution. The primary objective of this work is to analyze the relationship among the cloud configuration parameters (Number of VM, Type of VM, VM configurations) for executing scientific workflow applications in cloud platform. In this work, to accurately analyze the influence of cloud platform resource configuration and scheduling polices a new predictive modelling using Box–Behnken design which is one of the modelling technique of Response Surface Methodology (RSM). It is used to build quadratic mathematical models that can be used to analyze relationships among input and output variables. Workflow cost and makespan models were built for real world scientific workflows using ANOVA and it was observed that the models fit well and can be useful in analyzing the performance of scientific workflow applications in cloud



中文翻译:

响应面建模用于科学工作流在云中的性能分析

科学家使用科学的工作流应用程序在物理,化学,天文学等各个领域进行研究。这些应用程序需要大量的计算资源,并且当前使用云平台来有效地运行这些应用程序。为了提高云平台中工作流程执行的能力和成本,它需要标识适当数量的虚拟机(VM)并选择适当的VM类型。由于云平台是动态的,因此可用资源和资源类型是影响工作流程执行成本和有效期的两个重要因素。这项工作的主要目的是分析云配置参数(VM数量,VM类型,VM配置)之间的关系,以便在云平台上执行科学工作流程应用程序。在这项工作中 为了精确分析云平台资源配置的影响和调度策略,使用了Box–Behnken设计的一种新的预测模型,该模型是响应面方法(RSM)的建模技术之一。它用于建立二次数学模型,可用于分析输入和输出变量之间的关系。使用ANOVA为现实世界中的科学工作流构建了工作流成本和makepan模型,并观察到该模型非常合适,可用于分析云中科学工作流应用程序的性能 它用于建立二次数学模型,可用于分析输入和输出变量之间的关系。使用ANOVA为现实世界中的科学工作流构建了工作流成本和makepan模型,并观察到该模型非常合适,可用于分析云中科学工作流应用程序的性能 它用于建立二次数学模型,可用于分析输入和输出变量之间的关系。使用ANOVA为现实世界中的科学工作流构建了工作流成本和makepan模型,并观察到该模型非常合适,可用于分析云中科学工作流应用程序的性能

更新日期:2020-09-10
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