Load Balancing in Cloud Computing with Enhanced Genetic Algorithm
Kalpana1, Manjula Shanbhog2
1Kalpana, IILM Academy of Higher Learning College of Engineering & Technology, Greater Noida (U.P), India.
2Manjula Shanbhog, IILM Academy of Higher Learning College of Engineering & Technology, Greater Noida (U.P), India.
Manuscript received on 24 August 2019 | Revised Manuscript received on 05 September 2019 | Manuscript Published on 16 September 2019 | PP: 926-930 | Volume-8 Issue-2S6 July 2019 | Retrieval Number: B11760782S619/2019©BEIESP | DOI: 10.35940/ijrte.B1176.0782S619
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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: Cloud computing has a decentralized architecture in which virtual machine migration is one of the major challenges which affects the network performance. To balance the network load, various techniques are designed for the virtual machine migration. In the previous research work, genetic algorithm was proposed for Virtual Machine (VM) migration which can balance the network load. The genetic algorithm is complex in nature which increases the execution time. In this research work, genetic algorithm is improved for VM migration which reduces the execution time and also space and bandwidth utilization.
Keywords: Genetic Algorithm, Virtual Machine Migration, Bandwidth Utilization.
Scope of the Article: Cloud Computing