Qos Ranking Prediction Framework For Cloud Services

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QoS Ranking Prediction Framework for Cloud Services J.Subathra Department of Information Technology B.S.Abdur Rahman University Chennai, Tamilnadu Email:Subathrait.jeeva24@gmail.com Ms. P. Latchoumy Department of information technology B.S.Abdur Rahman University Chennai, Tamilnadu Email:lak75dhana@gmail.com Abstract— The rising popularity of cloud computing makes building high quality cloud applications a critical and urgently required research problem. QoS rankings provide valuable information for making optimal cloud service selection from a set of functionally equivalent service candidates. To obtain QoS values, real-world invocations on the service candidates are usually required. The existing system focuses on QoS ranking prediction for cloud services by taking advantage of the past service usage experiences of other consumers. This framework requires no additional invocations of cloud services when making QoS ranking prediction. Two personalized QoS ranking prediction approaches are proposed to predict the QoS rankings directly. The Proposed system is designed to improve the ranking accuracy of the approaches by exploiting additional techniques. When a user has multiple invocations of a cloud service at different time, the proposed will explore selection ranking prediction approaches for cloud services by employing information of service users and cloud services. Selection ranking prediction approach provides reliable service to the user. Index

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