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Energy-efficient Virtual Machine Allocation Technique Using Flower Pollination Algorithm in Cloud Datacenter:A Panacea to Green Computing

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Journal of Bionic Engineering 2019年第2期16卷 354-366页

作者： Mohammed Joda Usman Abdul Samad Ismail Hassan Chizari Gaddafi Abdul-Salaam Ali Muhammad Usman abdulsalam yau gital Omprakash Kaiwartya Ahmed Aliyu Department of Maths Bauchi State University GadauBauchi 81007Nigeria Department of Computer Science Universiti Teknology MalaysiaSkudai Johor 81310Malaysia School of Computing and Technology Park CampusUniversity of Gloucestershire Cheltenham GL50 4SHUK Department of Computer Science Kwame Nkrumah University of Science and TechnologyKumasi 00233Ghana Department of Maths and Computer Federal College of Education Technical GombeGombe 072158Nigeria Department of Maths Abubakar Tafawa Balewa University BauchiBauchi 81027Nigeria Department of Computer and Information Technology Northumbria UniversityNewcastle NE1SSTUK

Cloud computing has attracted significant interest due to the increasing service demands from organizations offloading computationally intensive tasks to ***,datacenter infrastructure comprises hardware resources that consume high amount of energy and give out carbon emissions at hazardous *** cloud datacenter,Virtual Machines(VMs)need to be allocated on various Physical Machines(PMs)in order to minimize resource wastage and increase energy *** allocation problem is *** finding an exact solution is complicated especially for large-scale *** this con text,this paper proposes an Energy-oriented Flower Pollination Algorithm(E-FPA)for VM allocation in cloud datacenter environments.A system framework for the scheme was developed to enable energy-oriented allocation of various VMs on a *** allocation uses a strategy called Dynamic Switching Probability(DSP).The framework finds a near optimal solution quickly and balances the exploration of the global search and exploitation of the local *** considers a processor,storage,and memory constraints of a PM while prioritizing energy-oriented allocation for a set of *** performed on MultiRecCloudSim utilizing planet workload show that the E-FPA outperforms the Genetic Algorithm for Power-Aware(GAPA)by 21.8%,Order of Exchange Migration(OEM)ant colony system by 21.5%,and First Fit Decreasing(FFD)by 24.9%.Therefore,E-FPA significantly improves datacenter performance and thus,enhances environmental sustainability.

关键词： virtualization green computing cloud datacenter energy optimization

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