International Journal of Advances in Computer Science and Cloud Computing (IJACSCC)
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current issues
Volume-7,Issue-2  ( Nov, 2019 )
Statistics report
Oct. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 14
Paper Published : 149
No. of Authors : 381
  Journal Paper

Paper Title
Improved Genetic Algorithm for Load Balancing in Cloud Computing

Abstract
Cloud computing as a computing paradigm offers a lot of services in-order to reduce the difficulties induced due to on-site computing. These constraints include limited storage, processing power, bandwidth, resources etc. Implementing and providing cloud service face several challenges. One of the main challenges is the task scheduling, which is the mapping of incoming user request to virtual machine (VM). This can be solved using either hard-computing methods or soft-computing methods. In this paper, we propose a method which is based on Genetic algorithm, which can be used to find optimum mapping solution between task and VM. Metrics which can be used to evaluate different strategies are response time, cost, overall execution time etc. Our simulation on cloudsim shows promising results. Keywords - Cloud Computing, Load Balancing, Cloudsim, Genetic Algorithm


Author - Sreeraj S, Josna V R

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| Published on 2019-12-30
   
   
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