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Virtual machine power measuring technique with bounded error in cloud environments

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SKU: PROJ1184 Categories: 2013 Projects, 2014 Projects, Final Year Projects, Online Java Projects, Parallel and Distributed Projects Tags: academic projects, Android project 2013-2014, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project Abstract, dotnet project list, Final Year Projects, ieee abstracts, ieee paper download, ieee projects 2013, ieee projects 2013 paper list, ieee projects 2013-2014, ieee projects 2014, ieee projects 2014 paper list, ieee projects 2015, ieee projects 2015 paper list., ieee titles, java project list, java projects 2013-2014, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project Abstract, Vlsi project list
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Virtual machine power measuring technique with bounded error in cloud environments

 

Abstract— Virtual machine power measuring technique with bounded error in cloud environments. Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of CPU cores or more. In this paper, we investigate ways to support these scientific workflows in a heterogeneous environment in which cluster computing resources are integrating with cloud computing resources. Specifically, we first propose an architecture that utilizes cloud resources to address load balancing issues. For that, the proposed architecture measures the status < Final Year Projects > of job queue on the front-end node, and then dynamically creates virtual machines from cloud pools based on the measured results to expand computing resource of the cluster. Next, we present experiment results of computational performance in hybrid infrastructure where the virtual and physical nodes are mixed.

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