Knee Point-Driven Bottleneck Detection Algorithm for Cloud Service System

摘要：

　　Currently,providers of Software as a service (SaaS) can use Infrastructure as a Service (IaaS) to obtain the resources required for serving customers.Performance problems in a SaaS system are difficult to diagnose,because they may be caused by various system components.This study proposes a knee point-driven bottleneck detection algorithm,the specific resource bottleneck in the target system can be detected by analyzing the collected metrics.The detection result provides a scale up recommendation for the service provider to facilitate reconfiguring the service system.The experimental results revealed that the proposed system can detect a potential bottleneck in a service system accurately.After solving the detected bottleneck the performance of the target cloud service can be improved efficiently.

关键词： Bottleneck detection Knee point Cloud testing Resource allocation

作者: Xiao-Long Liu Xue-Bai Zhang Hsiang Chao Shyan-Ming Yuan

作者单位: Department of Computer Science,National Chiao Tung University,Hsinchu,Taiwan,ROC

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 102-111

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）