Virtualized Load Balancer for Hybrid Cloud Using Genetic Algorithm

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.

Automated summary

This paper proposes a virtualized genetic algorithm to provide balanced virtual machine services in a hybrid cloud. The algorithm is implemented using a cloud simulator and compared with existing load balancing techniques using metrics such as response time, throughput, and turnaround time.