An Analysis on ECSE Load Balancing Algorithm With CDC as a Service Broker Policy in Cloud with Heterogeneous Communication and Device Characteristics
Kumar PJ1, J.Prabhu2, N.Sivakumar3, P.S.Ramesh4, Suganya P5
1Dr Kumar PJ, Assistant Professor, [SG], School of Information Technology and Engineering, VIT, Vellore, (Tamil Nadu) India.
2Dr J.Prabhu, Associate Professor, School of Information Technology and Engineering, VIT, Vellore, (Tamil Nadu) India.
3Dr N.Sivakumar, Assistant Professor [SG], School of Information Technology and Engineering, VIT, Vellore, (Tamil Nadu) India.
4Prof. P.S.Ramesh, Assistant Professor [SG], School of Information Technology and Engineering, VIT, Vellore, (Tamil Nadu) India.
5Prof. Suganya P., Assistant Professor , School of Information Technology and Engineering, VIT, Vellore, (Tamil Nadu) India.
Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1631-1635 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8274078919/19©BEIESP | DOI: 10.35940/ijitee.I8274.078919
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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: Load balancing algorithms and service broker policies plays a crucial role in determining the performance of cloud systems. User response time and data center request servicing time are largely affected by the load balancing algorithms and service broker policies. Several load balancing algorithms and service broker polices exist in the literature to perform the data center allocation and virtual machine allocation for the given set of user requests. In this paper, we investigate the performance of equally spread current execution (ESCE) based load balancing algorithm with closest data center(CDC) service broker policy in a cloud environment that consists of homogeneous and heterogeneous device characteristics in data centers and heterogeneous communication bandwidth that exist between different regions where cloud data centers are deployed. We performed a simulation using CloudAnalyst an open source software with different settings of device characteristics and bandwidth. The user response time and data center request servicing time are found considerably less in heterogeneous environment.
Keywords: Data Centers, Virtual Machines, Load Balancing, Closest Data Center, Equally spread current Execution (ESCE)
Scope of the Article: Predictive Analysis