Optimization Load Balancing Over an Imbalance Datacenter Topologies
K Siva Tharun1, K. Kottilingam2
1K Siva Tharun, PG Scholar, Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, India.
2Dr. K. Kottilingam, Associate Professor, Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, India.
Manuscript received on 16 August 2019. | Revised Manuscript received on 21 August 2019. | Manuscript published on 30 September 2019. | PP: 5676-5680 | Volume-8 Issue-3 September 2019 | Retrieval Number: B2487078219/2019©BEIESP | DOI: 10.35940/ijrte.B2487.098319
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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 quick demand of cloud resources, responsible for design a highly dynamic and flexible Cloud, has become a main challenge in datacenter deployment.A huge number of virtual machines will be available in Datacenter. Further Datacenter will be divided into a greater number of clusters. Each cluster is grouped to same type of Virtual machines. The virtual machines inside the cluster is homogeneous and heterogeneous to other cluster. Any virtual machine can be allocated to end user. If an unhealthy and less energy virtual machine is allocated to user, it will completely degrade the performance of the machine. To overcome this issue, we use an efficient load-balancing algorithm to allocate virtual machine to end user. The Fuzzy Optimized load-balancing algorithm uses the bandwidth, memory, CPU utilization are the key metrics. An efficient algorithm increases the number of hosts allocated to each end user.
Index Terms: Datacenter, Memory, CPU, Bandwidth, Fuzzy, Load Balancing..
Scope of the Article: Cross-Layer Optimization