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學術出版;;Publications

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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Yuan, Shyan-MingSubject: search.filters.subject.Cloud computing

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    Auto-Scaling Mechanism for Cloud Resource Management Based on Client-Side Turnaround Time
    (2016)
    Liu, Xiao-Long
    ;
    Yuan, Shyan-Ming
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    Luo, Guo-Heng
    ;
    Huang, Hao-Yu
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    資訊工程學系
    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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    Implementing a Workflow Agent on Federated Cloud
    (2015)
    Jhu, Syuan-Ru
    ;
    Fan, Chih-Tien
    ;
    Yuan, Shyan-Ming
    ;
    Chang, Yue-Shan
    ;
    資訊工程學系
    Workflow scheduling is the way to schedule the complex scientific workflow. In a cloud platform, the resources can be utilized more effectively and efficiently by scheduling the workflow properly. In this paper, an agent-based workflow scheduling mechanism on cloud environment is proposed. We implement a set of agents that can federate multiple clouds and automatically monitor the entire system, and manage the job if it\'s a workflow job. We also implement a dynamic job dispatching algorithm to reduce the VM usage amount and improve the resource utilization.