Abstract
This paper presents an adaptive fuzzy-based cloud service brokering algorithm (AFBSB). The proposed algorithm employs an adaptive fuzzy-based engine to select the most appropriate data center for user cloud service requests considering user preferences in terms of cost and performance. The algorithm is implemented using an open-source cloud computing simulation tool. The algorithm results are tested against the results of other existing techniques within two types of cloud environments. First, a performance-constrained environment in which performance improvement is the main objective for cloud users. Second, a preference-aware environment, in which cloud users have different cost and performance preferences. Simulation results show that the proposed algorithm can achieve significant performance improvement in performance-constrained environments. As for the preference-aware environment, they show that AFBSB can operate in user-oriented manner that guarantees performance/cost improvement, as compared to other algorithms.
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