A Web Performance Modeling Process Based on the Methodology of Learning from Data

摘要：

Accurate performance metric models are the key to web capacity planning related problems. Due to the complexity of web systems, analytical modeling without integrating the performance testing process is not enough to get accurate metric models. To integrate performance testing and analytical modeling in a systematic way, a web performance modeling process is presented based on the methodology of learning from data. The process divides the modeling activity into several phases: constructing models and hypothetical conditions, deriving test cases, estimating parameters and validating models, etc. The scalability of a real web community system (www.igroot.com) is studied by using the proposed process. The error of estimated saturation point is within 1 percent, the error of estimated lower bound of buckle point is within 5 percent. At last, a HTTP processing bottleneck at the architecture level is identified by correlating the model with the threads data of the web server.

关键词： Performance modeling learning from data general linear regression analysis unified scalability model.

作者: Jianfei Yin Zhong Ming Zhijiao Xiao Hui Wang

作者单位: Software College of Shenzhen University, Shenzhen 518060, P.R. China

会议类型: 国际会议

会议名称: The 9th International Conference for Young Computer Scientists(第九届国际青年计算机大会)

会议地点: 安徽黄山

会议语种:英文

页码: 1285-1291

在线出版日期: 2008-11-18（万方平台首次上网日期，不代表论文的发表时间）