Response Surface Modelling for Performance Analysis of Scientific Workflow Application in Cloud

被引：0

作者：

Prathibha Soma

B. Latha

机构：

[1] Sri Sai Ram Engineering College,Department of Information Technology

[2] Anna University,Department of Computer Science and Engineering

[3] Sri Sai Ram Engineering College,undefined

[4] Anna University,undefined

来源：

Cluster Computing | 2021年 / 24卷

关键词：

Cloud computing; Scientific workflow application; Virtual machine; Modelling; Response surface methodology;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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

引用

页码：1123 / 1134

页数：11

共 36 条

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