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  1. Home
  2. Volume 7, Issue 8
  3. Authors

Online ISSN: 2515-8260

Volume7, Issue8

An Efficient Job Scheduling And Load Balancing Methods Using Enhanced Genetic Algorithm

    J. Santhosh R. Aruna P. Balamurugan G. Arulkumaran

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 8, Pages 4502-4510

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Abstract

This article proposes a new method for workflow scheduling hassle in the cell computing
surroundings which makes use of the optimization based totally scheduling with
environment friendly outcome. The portable framework is considerably much less
consistent than the wired condition; energy ought to be regarded at the planning time. Job
scheduling in cell grids therefore require a strong machine mannequin that can contain all
these factors. In order to assemble the vibrant and mobile nature of resources, the
availability has to be estimated in case of scheduling. In Grid Booster Algorithm’s is used
to time table the approach to allow wonderful load balancing.
Keywords:
    Genetic Algorithm (GA) Virtual Machine (VM) Variable Neighborhood Search (VNS)
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(2021). An Efficient Job Scheduling And Load Balancing Methods Using Enhanced Genetic Algorithm. European Journal of Molecular & Clinical Medicine, 7(8), 4502-4510.
J. Santhosh; R. Aruna; P. Balamurugan; G. Arulkumaran. "An Efficient Job Scheduling And Load Balancing Methods Using Enhanced Genetic Algorithm". European Journal of Molecular & Clinical Medicine, 7, 8, 2021, 4502-4510.
(2021). 'An Efficient Job Scheduling And Load Balancing Methods Using Enhanced Genetic Algorithm', European Journal of Molecular & Clinical Medicine, 7(8), pp. 4502-4510.
An Efficient Job Scheduling And Load Balancing Methods Using Enhanced Genetic Algorithm. European Journal of Molecular & Clinical Medicine, 2021; 7(8): 4502-4510.
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