Towards cloud-based resource management for big data applications

In the age of information technology, analyzing data in the cloud through efficient resource management is recognized as an effective solution to meet the quality-of-service needs of users. In this regard, this paper proposes a fuzzy selector-based approach to improve the virtual machine (VM) migration process that provides a balance between servers during the processing of tasks. The proposed approach is a hierarchical resource prediction that includes local and global parts for processing requests. Evaluations demonstrate the superiority of the proposed approach over state-of-the-art methods. The results show that the proposed approach reduces the cost by 10% compared to FAHP.