Implementing TaaS-based stress testing by MapReduce computing model

Gwan-Hwan Hwang, Chi Wu-Lee, Yuan-Hsin Tung, Chih-Ju Chuang, Syz-Feng Wu
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引用次数: 7

Abstract

In this paper we propose to employ the MapReduce computing model to implement a Testing as a Service (TaaS) for stress testing. We focus on stress testing for heavy-weight network transactions. The computation power of MapReduce computing system is used to simulate concurrent network transactions issued by a lot of users. The user first describes the testing scenario which he wants to be simulate in a testing script. The TaaS platform analyzes the testing script and then automatically distributes required testing data including details of transactions and files into a MapReduce computing system. We propose three different schemes to distribute testing data and measure their performances. We compare them with the popular stress testing tool JMeter and find out that our scheme can always have the tested system deliver higher error rate during the stress testing.
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利用MapReduce计算模型实现基于taas的压力测试
在本文中,我们建议使用MapReduce计算模型来实现压力测试的测试即服务(TaaS)。我们专注于对重量级网络事务进行压力测试。利用MapReduce计算系统的计算能力,模拟由大量用户发出的并发网络事务。用户首先描述他想在测试脚本中模拟的测试场景。TaaS平台对测试脚本进行分析,然后自动将所需的测试数据(包括事务细节和文件)分发到MapReduce计算系统中。我们提出了三种不同的方案来分发测试数据和衡量它们的性能。我们将它们与流行的压力测试工具JMeter进行了比较,发现我们的方案在压力测试中总能使被测系统提供更高的错误率。
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