Title: Auto-Scaling Mechanism for Cloud Resource Management Based on Client-Side Turnaround Time
Authors: Liu, Xiao-Long
Yuan, Shyan-Ming
Luo, Guo-Heng
Huang, Hao-Yu
Department of Computer Science
Keywords: Auto scaling;Cloud computing;Turnaround time;Resource management
Issue Date: 2016
Abstract: 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
ISBN: 978-3-319-23207-2
ISSN: 2194-5357
DOI: 10.1007/978-3-319-23207-2_21
Volume: 388
Begin Page: 209
End Page: 219
Appears in Collections:Conferences Paper