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.
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Liu, XL., Yuan, SM., Luo, GH., Huang, HY. (2016). Auto-Scaling Mechanism for Cloud Resource Management Based on Client-Side Turnaround Time. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. GEC 2015. Advances in Intelligent Systems and Computing, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-319-23207-2_21
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DOI: https://doi.org/10.1007/978-3-319-23207-2_21
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