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R&D: OUTFIT Optimal Data Storage Hosting Model Using Sugeno-Type Fuzzy Inference System for Multi-Cloud Environments

Proposed approach to categorize various cloud service providers with optimal grading process by including multiple decision criteria for fine-grained storage type selection

Journal of Intelligent & Fuzzy Systems has published an article written by Sujatha, M, Geetha, K., School of Computing, SASTRA Deemed to be University, Thanjavur, India, Vellore, India, Balakrishnan, P., SCOPE, VIT, Vellore, India, and Renugadevi, T, School of Computing, SASTRA Deemed to be University, Thanjavur, India.

Abstract:The unprecedented growth in personal, business and research data motivate the users to lease storages 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 the 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 exhibit itself as a better selection tool in comparison with its counterpart tools like Cloudorado, RightCloudz in terms of cost.

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