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Flexible load distribution for hybrid distributed virtual environments

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SKU: PROJ1196 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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Flexible load distribution for hybrid distributed virtual environments

Abstract— Flexible load distribution for hybrid distributed virtual environments.We propose a hybrid scheduling algorithm for load balancing in a distributed environment by combining the methodology of Divide-and-Conquer and Throttled algorithms referred to as DCBT. Our algorithm plays an important role in distributing the incoming load in an efficient manner so that it maximizes resource utilization in a cloud environment. Further, load balancer plays an important role in cloud environment by assigning incoming tasks to Virtual Machines (VM) intelligently. The main aim of the proposed DCBT is to reduce the total execution time of the tasks and thereby maximizing the resource utilization. Further, the proposed DCBT algorithm is analyzed using Cloud Sim simulator and also in < Final Year Projects > customized distributed environment using python. Experimental results demonstrate that the proposed algorithm gives better efficiency in both Cloud Sim and customized environments. The proposed DCBT utilizes the Virtual Machines more efficiently while reducing the execution time of the tasks allocated to Request Handlers (RH) by 9.972% in comparison to the Modified Throttled algorithm.

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