標題: Knee Point-Driven Bottleneck Detection Algorithm for Cloud Service System
作者: Liu, Xiao-Long
Zhang, Xue-Bai
Chao, Hsiang
Yuan, Shyan-Ming
資訊工程學系
Department of Computer Science
關鍵字: Bottleneck detection;Knee point;Cloud testing;Resource allocation
公開日期: 2016
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.
URI: http://dx.doi.org/10.1007/978-3-319-45835-9_9
http://hdl.handle.net/11536/136414
ISBN: 978-3-319-45834-2
978-3-319-45835-9
ISSN: 0302-9743
DOI: 10.1007/978-3-319-45835-9_9
期刊: Web Technologies and Applications: APWeb 2016 Workshops, WDMA, GAP, and SDMA
Volume: 9865
起始頁: 102
結束頁: 111
Appears in Collections:Conferences Paper