Adaptive user-oriented fuzzy-based service broker for cloud services

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. (c) 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This paper presents an adaptive fuzzy-based cloud service brokering algorithm (AFBSB) that selects the most appropriate data center for user cloud service requests based on user preferences in terms of cost and performance. The algorithm achieves significant performance improvement in performance-constrained environments and operates in a user-oriented manner in preference-aware environments.