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Virtualized Load Balancer for Hybrid Cloud Using Genetic Algorithm

S. Manikandan1,*, M. Chinnadurai2
1 Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, 611 002, India
2 Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611 002, India
* Corresponding Author: S. Manikandan. Email:

Intelligent Automation & Soft Computing 2022, 32(3), 1459-1466. https://doi.org/10.32604/iasc.2022.022527

Received 10 August 2021; Accepted 13 September 2021; Issue published 09 December 2021

Abstract

Load Balancing is an important factor handling resource during running and execution time in real time applications. Virtual machines are used for dynamically access and share the resources. As per current scenario cloud computing is played major for storage, resource accessing, resource pooling and internet based service offering. Usage of cloud computing services is dynamically increased such as online shopping, education, ticketing, etc. Many users can use the cloud resources and load balancing is used for adjusting the virtual machine and balance the node. Our proposed virtualized genetic algorithms are to provide balanced virtual machine services in Hybrid cloud. The proposed algorithm and experiments are implemented by using Cloud simulator. In this paper the experiments are done with cloud computing models, Virtual Machine allocation, load balancing and simulations. Also compare the results using response time, throughput and turnaround time using cloud sim. The accuracy can be compared with existing load balancing techniques.

Keywords

Load balancing; hybrid cloud; virtual machine; genetic algorithm; cloud simulator

Cite This Article

S. Manikandan and M. Chinnadurai, "Virtualized load balancer for hybrid cloud using genetic algorithm," Intelligent Automation & Soft Computing, vol. 32, no.3, pp. 1459–1466, 2022.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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