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Multiobjective Level-Wise Scientific Workflow Optimization in IaaS Public Cloud Environment

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タイトル: Multiobjective Level-Wise Scientific Workflow Optimization in IaaS Public Cloud Environment
著者: Thant, Phyo Thandar 著作を一覧する
Powell, Courtney 著作を一覧する
Schlueter, Martin 著作を一覧する
Munetomo, Masaharu 著作を一覧する
発行日: 2017年12月21日
出版者: Hindawi Publishing Corporation
誌名: Scientific programming
開始ページ: 5342727
出版社 DOI: 10.1155/2017/5342727
抄録: Cloud computing in the field of scientific applications such as scientific big data processing and big data analytics has become popular because of its service oriented model that provides a pool of abstracted, virtualized, dynamically scalable computing resources and services on demand over the Internet. However, resource selection to make the right choice of instances for a certain application of interest is a challenging problem for researchers. In addition, providing services with optimal performance at the lowest financial resource deployment cost based on users' resource selection is quite challenging for cloud service providers. Consequently, it is necessary to develop an optimization system that can provide benefits to both users and service providers. In this paper, we conduct scientific workflow optimization on three perspectives: makespan minimization, virtual machine deployment cost minimization, and virtual machine failure minimization in the cloud infrastructure in a level-wise manner. Further, balanced task assignment to the virtual machine instances at each level of the workflow is also considered. Finally, system efficiency verification is conducted through evaluation of the results with different multiobjective optimization algorithms such as SPEA2 and NSGA-II.
資料タイプ: article
URI: http://hdl.handle.net/2115/68288
出現コレクション:雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

提供者: Phyo Thandar Thant

 

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