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Issue title: Special section: Soft Computing and Intelligent Systems: Techniques and Applications
Guest editors: Sabu M. Thampi, El-Sayed M. El-Alfy and Ljiljana Trajkovic
Article type: Research Article
Authors: Sujatha, M.a | Geetha, K.a; * | Balakrishnan, P.b | Renugadevi, T.a
Affiliations: [a] School of Computing, SASTRA Deemed to be University, Thanjavur, India | [b] SCOPE, VIT, Vellore, India
Correspondence: [*] Corresponding author. K. Geetha, School of Computing, SASTRA Deemed to be University, Thanjavur, India. E-mail: geetha@cse.sastra.edu.
Abstract: The unprecedented growth in personal, business and research data motivates users to lease storage from multiple cloud storage providers like Amazon, Azure, etc. Selection of cost-effective cloud storage service by considering different pricing policies along with their performance characteristics is a challenging task. This research proposes a model named as OUTFIT (Optimal sUgeno Type Fuzzy Inference sysTem) an optimal data storage hosting model by suggesting an appropriate storage type based on user demands. In the first phase, we have surveyed Amazon, Google Cloud, Azure and Rackspace cloud storage providers and consolidated the different cloud storage types supported by them. In the second phase the cloud service providers are ranked by using Sugeno fuzzy inference system based on the user preference. The third phase designates the appropriate service that incurs minimal estimated storage usage cost. The proposed approach is able to categorize various cloud service providers with an optimal grading process by including multiple decision criteria for fine-grained storage type selection. The observed results prove it to be a more favourable selection tool in comparison with its counterpart tools like Cloudorado, RightCloudz in terms of cost.
Keywords: CSP selection, QoS Attributes, Sugeno Inference system, Iaas storage selection, Cloud computing
DOI: 10.3233/JIFS-179739
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 6595-6605, 2020
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