An Intelligent Genetic Base Algorithm for Optimal Virtual Machine Migration in Cloud Computing
Neha Sharma1, Jaspreet Singh2, Lokesh Pawar3
1Neha Sharma, M. tech (Computer Science Engineering) Scholar Chandigarh University Mohali, Punjab, India.
2Jaspreet Singh, Department of Computer Science Engineering, Chandigarh University Mohali, Punjab, India.
3Lokesh Pawar, Department of Computer Science Engineering, Chandigarh University Mohali, Punjab, India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 27 May 2019 | Manuscript published on 30 May 2019 | PP: 2538-2543 | Volume-8 Issue-1, May 2019 | Retrieval Number: A2206058119/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The cloud computing is the architecture in which virtual machines are involved and connect with the cloud service provider. The virtual machines connect with the cloud service provider on behalf of the users Nowadays load balancing is very big issues to solve this issue various load balancing approaches are proposed. The virtual machines get overburden due to uncertainties and to handle this challenge the genetic algorithms is applied for virtual machine migration in cloud environment. In this research work, the proposed algorithm is applied for virtual machine migration and outcomes are correlated with the existing used genetic algorithm in terms of latency, bandwidth utilization, and space utilization. The results show that our proposed approach achieves better performance for cloud user and maximal profits for cloud providers by doing optimal virtual machine migration.
Keywords: Genetic Algorithm, Intelligent Genetic Algorithm (IGA), Optimal Migration Using Genetic Algorithm
Scope of the Article: Cloud Computing