Data stable aggregation algorithm based on fuzzy algorithm in cloud computing

作     者：Wang, Yu 

作者机构：Hanjiang Normal Univ Dept Comp Sci Shiyan 442000 Peoples R China 

出 版 物：《JOURNAL OF INTELLIGENT & FUZZY SYSTEMS》 (智能与模糊系统杂志)

年 卷 期：2020年第38卷第6期

页      面：7935-7944页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Science and technology research project of Hubei Provincial Education Department [B2017217] 

主　　题：Cloud computing fuzzy algorithm data stable convergence clustering 

摘      要：In order to improve the ability of cloud computing data scheduling, this paper proposes a new method for multi-task, multi-level cloud computing data aggregation based on fuzzy association feature extraction. Heterogeneous directed graph analysis method is used to design cloud computing data. The semantic correlation fusion method is used to implement cloud computing data feature extraction and adaptive scheduling. The fuzzy clustering is used to process the characteristic amount of cloud computing data, and the optimal aggregation of cloud computing data is realized. Simulation results show that the method has a higher recall rate for multi-task and multi-level cloud data aggregation, and the highest recall rate can reach 1, which improves the accuracy of resource aggregation.