Multi Objective Ant colony Optimization Algorithm for Resource Allocation in Cloud Computing
Prasad Devarasetty1, Ch. Satyananda Reddy2
1Prasad Devarasetty, Department of Computer Science and Engineering, DVR & Dr HS MIC College of Technology, Vijayawada, Andhra Pradesh, India.
2Dr. Ch. Satyananda Reddy, Department of Computer Science and Systems Engineering, AU College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.
Manuscript received on 01 December 2018 | Revised Manuscript received on 06 December 2018 | Manuscript Published on 26 December 2018 | PP: 68-73 | Volume-8 Issue- 2S2 December 2018 | Retrieval Number: BS2012128218/19©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: Cloud computing provides the services based on the pay-as-you-use policy. The more utilization of services leads to the utilization of more number of data centres. Therefore, data centres require high energy consumption for computing the tasks. To improve the efficiency of the data centre, resource management using the virtualization technology is the crucial factor. This paper concentrates on the issue of virtual machine placement and also proposes the bio inspired approach for reducing the resource wastage, minimize the energy consumption and communication cost with in the data centre. Ant Colony Optimization (ACO) algorithm is proposed to obtain the solution set for multi-objective problem. The performance of the proposed algorithm is tested with the existing algorithms and it is proved that the proposed algorithm is efficient in terms of energy consumption, communication cost and resource utilization.
Keywords: Virtual Placement, Cloud, Consolidation, Communication Cost, Resources.
Scope of the Article: Communication