Cloud service provider evaluation system using fuzzy rough set technique

Abstract

Cloud Service Provider (CSP) offers a wide variety of scalable, flexible, and cost-efficient services to users on demand and pay-per-utilization basis. However, vast diversity in available services leads to various challenges for a user to determine and select the best suitable service. Further, sometime user needs to hire required services from multiple service providers which leads to account, security, support, interface, and Service Level Agreements (SLAs) associated management difficulties. To avoid such problems having a Cloud Service Broker (CSB) which is aware of service offerings and user's Quality of Service (QoS) requirements will benefit both the service providers and users. We have proposed a cloud service brokerage architecture using fuzzy rough set technique, which facilitates ranking and selecting services, based on users QoS requirements and finally monitor the service execution. We have used fuzzy rough set technique for dimension reduction and weighted Euclidean distance to rank the service providers. To prioritize user QoS request, we suggest to use user assign weights. We also incorporate system assigned weights to give the relative importance to QoS attributes. We compared the proposed ranking technique with an existing technique based on the system response time. With the help of a case study, we have demonstrated the efficiency of the proposed technique. The case study experiment results show that the proposed approach is scalable, resilience, and produce better results with less searching time.