A fuzzy-based decision-making broker for effective identification and selection of cloud infrastructure services

In a typical cloud environment, the task of identification and selection of required services solely depend upon the service specification furnished by the cloud user. The experienced users can specify their service requirements in precise terms by using numerical representations. On the other end, the task of service specification is always a challenging one for an inexperienced cloud user who seems to be new to the environment. In such a kind of requirement, vagueness arises in the preliminary phase of cloud service life cycle results service mismatches and affects both the cloud providers and user significantly. Hence, identifying and offering suitable services in responses to the imprecise service requirement have been emerged as an important research issue. In this paper, we have proposed a fuzzy logic-based intelligent cloud broker that clears the imprecise state of the inexperienced cloud user while furnishing the infrastructure service requirements. The proposed broker acts as an intermediate layer between the provider and consumer that finds out the appropriate services through the fuzzification and de-fuzzification process. In addition, the broker performs service aggregation through Sugeno integral and makes decision about the right services by implementing the fuzzy decision tree. The effectiveness of the broker has been validated by using MATLAB and R Studio.