Research on information classification and storage in cloud computing data center based on group collaboration intelligent clustering

Web Intell. Pub Date : 2021-11-17 DOI:10.3233/web-210464
Linlin Zhang, Sujuan Zhang
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Abstract

In order to overcome the problems of long time and low accuracy of traditional methods, a cloud computing data center information classification and storage method based on group collaborative intelligent clustering was proposed. The cloud computing data center information is collected in real time through the information acquisition terminal, and the collected information is transmitted. The optimization function of information classification storage location was constructed by using the group collaborative intelligent clustering algorithm, and the optimal solutions of all storage locations were evolved to obtain the elite set. According to the information attribute characteristics, different information was allocated to different elite sets to realize the classified storage of information in the cloud computing data center. The experimental results show that the longest time of information classification storage is only 0.6 s, the highest information loss rate is 10.0%, and the highest accuracy rate is more than 80%.
基于群协作智能集群的云计算数据中心信息分类与存储研究
为了克服传统方法耗时长、准确率低的问题,提出了一种基于群体协同智能聚类的云计算数据中心信息分类存储方法。通过信息采集终端实时采集云计算数据中心信息,并将采集到的信息进行传输。利用群协同智能聚类算法构造信息分类存储位置的优化函数,并对所有存储位置的最优解进行演化,得到精英集。根据信息属性特征,将不同的信息分配到不同的精英集合中,实现信息在云计算数据中心的分类存储。实验结果表明,信息分类存储的最长时间仅为0.6 s,最高信息损失率为10.0%,最高准确率达80%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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