IJIRST (International Journal for Innovative Research in Science & Technology)ISSN (online) : 2349-6010

 International Journal for Innovative Research in Science & Technology

Power Efficient Management in Data Center Using Server Consolidation for Green Computing


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International Journal for Innovative Research in Science & Technology
Volume 1 Issue - 8
Year of Publication : 2015
Authors : R.Gnanasundaram ; S.Suresh

BibTeX:

@article{IJIRSTV1I8068,
     title={Power Efficient Management in Data Center Using Server Consolidation for Green Computing },
     author={R.Gnanasundaram and S.Suresh},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={8},
     pages={212--215},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I8068.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}



Abstract:

A Cloud computing has revolutionized the Information Technology industry by enabling elastic On-Demand provisioning of computing resources. Cloud data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon-di-oxide emissions. The goal is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. Virtual Machine consolidation leverages fine-grained fluctuations in the application workloads and continuously reallocates Virtual Machines to minimize the number of active physical nodes. Server virtualization is a prominent approach to consolidate applications from multiple applications to one server. With a growing concern on the considerable energy consumed by data centers, research efforts are targeting toward green data centers with higher energy efficiency. The results obtained have proved that Server Consolidation has greatly reduced the energy consumption without affecting the performance of the system.


Keywords:

Virtualisation, Energy Efficiency, Cloud Computing, Energy Consumption, Allocation of VM’s


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