Cloud Service Provider Evaluation System using Fuzzy Rough Set Technique
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Cloud Service Provider (CSPs) offers a wide variety of scalable, flexible, and cost-efficient services to the cloud customers on demand and pay-per-utilization. However, vast diversity in available cloud services leads to various challenges for users to determine and select the best suitable service. Also, sometimes users need to hire the required services from multiple CSPs which introduce difficulties in managing interfaces, accounts, security, supports, and Service Level Agreements (SLAs). To circumvent such problems having a Cloud Service Broker (CSB) be aware of service offerings and users Quality of Service (QoS) requirements will benefit both the CSPs as well as users. In this work, we proposed a Fuzzy Rough Set based Cloud Service Brokerage Architecture, which is responsible for ranking and selection of services based on users QoS requirements, and finally monitoring the service executions. We have used the fuzzy rough set technique for dimension reduction, and to rank the CSPs we have used weighted Euclidean distance. To prioritize user QoS request, we intended to use user assign weights, also incorporated system assigned weights to give the relative importance to QoS attributes. We compared the proposed ranking technique with an existing method based on the system response time taken. The case study experiment results show that the proposed approach is scalable, resilience, and produce better results with less searching time.
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