標題: | Auto-Scaling Mechanism for Cloud Resource Management Based on Client-Side Turnaround Time |
作者: | Liu, Xiao-Long Yuan, Shyan-Ming Luo, Guo-Heng Huang, Hao-Yu 資訊工程學系 Department of Computer Science |
關鍵字: | Auto scaling;Cloud computing;Turnaround time;Resource management |
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. SaaS providers can save substantially on costs by using resource-management techniques such as auto scaling. However, in most current auto-scaling methods, server-side system information is used for adjusting the amount of resources, which does not allow the overall service performance to be evaluated. In this paper, a novel auto-scaling mechanism is proposed for ensuring the stability of service performance from the client-side of view. In the proposed mechanism, turnaround time monitors are deployed as clients outside the service, and the information collected is used for driving a dynamic auto-scaling operation. A system is also designed to support the proposed auto scaling mechanism. The results of experiments show that using this mechanism, stable service quality can be ensured and, moreover, that a certain amount of quality variation can be handled in order to allow the stability of the service performance to be increased. |
URI: | http://dx.doi.org/10.1007/978-3-319-23207-2_21 http://hdl.handle.net/11536/135901 |
ISBN: | 978-3-319-23207-2 978-3-319-23206-5 |
ISSN: | 2194-5357 |
DOI: | 10.1007/978-3-319-23207-2_21 |
期刊: | GENETIC AND EVOLUTIONARY COMPUTING, VOL II |
Volume: | 388 |
起始頁: | 209 |
結束頁: | 219 |
Appears in Collections: | Conferences Paper |