Measurement-based performance analysis of e-commerce applications with Web services components

V. Datla, K. Goseva-Popstojanova
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引用次数: 35

Abstract

Web services are increasingly used to enable interoperability and flexible integration of e-business systems. In this paper we focus on measurement-based performance analysis of an e-commerce application which uses Web services components to execute business operations. In our experiments we use a session-oriented workload generated by a tool developed accordingly to the TPC-W specification. The empirical results are obtained for two different user profiles, Browsing and Ordering, under different workload intensities. Unlike the previous work which was focused on the overall server response time and throughput, we present Web interaction, software architecture, and hardware resource level analysis of the system performance. In particular, we propose a method for extracting component level response times from the application server logs and study the impact of Web services and other components on the server performance. The results show that the response times of Web services components increase significantly under higher workload intensities when compared to other components. From the hardware resource measurements it is obvious that the higher response times of Web services components are due to parsing XML messages and contention for database resources. The results of our study identify software components and hardware resources which are potential bottlenecks in the system and thus provide valuable information for capacity planning of e-commerce applications
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对带有Web服务组件的电子商务应用程序进行基于度量的性能分析
Web服务越来越多地用于实现电子商务系统的互操作性和灵活集成。在本文中,我们将重点关注使用Web服务组件执行业务操作的电子商务应用程序的基于度量的性能分析。在我们的实验中,我们使用由根据TPC-W规范开发的工具生成的面向会话的工作负载。在不同的工作负载强度下,对“浏览”和“订购”两种不同的用户配置进行了实证研究。与之前的工作不同的是,我们关注的是整个服务器的响应时间和吞吐量,我们提供了Web交互、软件架构和硬件资源级别的系统性能分析。特别地,我们提出了一种从应用服务器日志中提取组件级响应时间的方法,并研究Web服务和其他组件对服务器性能的影响。结果表明,与其他组件相比,在更高的工作负载强度下,Web服务组件的响应时间显著增加。从硬件资源测量可以明显看出,Web服务组件的响应时间较长是由于解析XML消息和争用数据库资源造成的。我们的研究结果确定了系统中潜在瓶颈的软件组件和硬件资源,从而为电子商务应用程序的容量规划提供了有价值的信息
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