完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Liu, Xiao-Long | en_US |
dc.contributor.author | Yuan, Shyan-Ming | en_US |
dc.contributor.author | Luo, Guo-Heng | en_US |
dc.contributor.author | Huang, Hao-Yu | en_US |
dc.date.accessioned | 2017-04-21T06:48:59Z | - |
dc.date.available | 2017-04-21T06:48:59Z | - |
dc.date.issued | 2016 | en_US |
dc.identifier.isbn | 978-3-319-23207-2 | en_US |
dc.identifier.isbn | 978-3-319-23206-5 | en_US |
dc.identifier.issn | 2194-5357 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1007/978-3-319-23207-2_21 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/135901 | - |
dc.description.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. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Auto scaling | en_US |
dc.subject | Cloud computing | en_US |
dc.subject | Turnaround time | en_US |
dc.subject | Resource management | en_US |
dc.title | Auto-Scaling Mechanism for Cloud Resource Management Based on Client-Side Turnaround Time | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.doi | 10.1007/978-3-319-23207-2_21 | en_US |
dc.identifier.journal | GENETIC AND EVOLUTIONARY COMPUTING, VOL II | en_US |
dc.citation.volume | 388 | en_US |
dc.citation.spage | 209 | en_US |
dc.citation.epage | 219 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000381875900021 | en_US |
dc.citation.woscount | 0 | en_US |
顯示於類別: | 會議論文 |