Cost Optimization Algorithm for Data Center Management in Cloud
K Sai Prasanthi1, A K Subash2, B Manoj3, P Sunil Kiran4
1K Sai Prasanthi*, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation (KLEF),Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, India.
2A K Subash, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation (KLEF),Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, India.
3B Manoj, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation (KLEF),Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, India.
4P Sunil Kiran, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation (KLEF),Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, India
Manuscript received on November 14, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 4777-4781 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7897129219/2019©BEIESP | DOI: 10.35940/ijitee.B7897.129219
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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: One of the main challenge in cloud is Cost Optimization. In cloud computing, the cloud providers usually calls CSP offer provisioning plans for the cloud consumers in the following two ways one is reservation plan(also referred as long term plan) and the other is on-demand plan(also referred as short term plan). In general, cost of computing asset provisioned by reservation plan is cheaper when compared to cost obtained by the on-demand plan, With the reservation plan, the consumer can reduce the total asset provisioning cost since cloud consumer has to pay to provider in advance. However, the best advance reservation of assets is difficult to be accomplish due to uncertainty of cloud consumer’s future demand and providers’ resource prices. To address this problem, an OCRP algorithm is proposed by formulating a SPI model. The OCRP algorithm can provision computing assets for being used in multiple provisioning stages as well as a long-term plan. The demand and price uncertainty is considered in OCRP. In this project, different approaches to obtain the solution of the OCRP algorithm are considered including DEF, SAA and Benders decomposition. Numerical the studies are extensively performed in which the outcomes clearly show that with the OCRP algorithm, cloud consumer can successfully minimize total cost of asset provisioning in cloud computing environments.
Keywords: OCRP, SPI, DEF, SAA, CSP
Scope of the Article: Algorithm Engineering