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Classical Probability Ranking Principle based Provider Selection in Federated Cloud
Background/Objective: An objective of reliable ranking method to encourage the growth of Cloud Computing. The challenges of probability ranking are various natures of cloud services and complexity of malicious ratings. Methods/Statistical Analysis: The proposed Classical Probability Ranking Principle (CPRP) is used to select the matched providers, rank it and choose the optimal provider for the service in federated cloud. In all situations, federated cloud presents list of provider to the users, with reference to which system to choose and allocate the best to the user. Each provider is associated with SMI attributes, based on attributes, an optimum ranking of the choices can be derived using CPRP. Findings: This chapter is discussed the new ranking mechanism for ranking the providers using classical probability ranking on the basis of the SMI attributes. All the shortlisted providers are examined and then ranking is done on the basis of the present and past values of SMI. Applications/Improvements: The future work on ranking manages with variation in QoS attributes that is presentation by adopt the evolutionary algorithms. This work also extends the feature model to non-theoretical QoS attributes.
Matched providers, optimal provider, Ranking, SMI attributes, SLA, CPRP.
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