Computer Science ›› 2017, Vol. 44 ›› Issue (5): 166-169.doi: 10.11896/j.issn.1002-137X.2017.05.029

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Segmented Fusion Fuzzy Clustering Algorithm for Cloud Data Security Storage

SHAN Dong-hong, SHI Yong-chang, ZHAO Wei-ting and ZHANG Jing-pu   

  • Online:2018-11-13 Published:2018-11-13

Abstract: In order to improve the safety performance of cloud data storage,the collection of attribute clustering data need to be optimized.Since the traditional method which uses fuzzy C means clustering classification of cloud data stora-ge design is sensitive to initial clustering center and is easy to fall into the local convergence,a method of constructing the cloud data security storage model was proposed based on segmentation fusion and fuzzy clustering.The data structure analysis of distribution grid structure model is given to build cloud data security storage and decomposition of vector quantization characteristics of cloud data attributes,cloud storage data on mass flow uses piecewise matching feature detection method to realize adaptive compression,redundant data collection and mining are realized,high order spectrum of cloud data stream is mined.Based on the fuzzy C means clustering algorithm,the data clustering fuzzy clustering is used to improve the security of data storage and reduce the load of cloud data storage.The simulation results show that the proposed method can reduce the error rate of data clustering and improve the throughput of data storage,and ensure the security of data storage.

Key words: Cloud data,Secure storage,Fusion,Fuzzy C means,Clustering

[1] BI A Q,WANG S T.Transfer Affinity Propagation Clustering Algorithm Based on Kullback-Leiber Distance[J].JEIT,2016,38(8):2076-2084.(in Chinese) 毕安琪,王士同.基于Kullback-Leiber距离的迁移仿射聚类算法[J].电子与信息学报,2016,38(8):2076-2084.
[2] LONG M,WANG J,DING G,et al.Adaptation regularization:A general framework for transfer learning[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(5):1076-1089.
[3] PATRICIA N,CAPUTO B.Learning to learn,from transferlearning to domain adaptation:A unifying perspective[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Columbus,OH,USA,2014:1442-1449.
[4] SUN L,GUO C H.Incremental affinity propagation clustering based on message passing[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(11):2731-2744.
[5] LING C G,WANG H Z.Optimization research on differentialevolution algorithm and its application in clustering analysis[J].Modern electronic technology,2016,39(13):103-107.(in Chinese) 梁聪刚,王鸿章.微分进化算法的优化研究及其在聚类分析中的应用[J].现代电子技术,2016,39(13):103-107.
[6] LI M D,ZHAO H,WENG X W,et al.Differential evolutionbased on optimal Gaussian random walk and individual selection strategies[J].Control and Decision,2016,31(8):1379-1386.(in Chinese) 李牧东,赵辉,翁兴伟,等.基于最优高斯随机游走和个体筛选策略的差分进化算法[J].控制与决策,2016,31(8):1379-1386.
[7] PATEL V M,NGUYEN H V,VIDAL R.Latent space sparse and low-rank subspace clustering[J].IEEE Journal of Selected Topics in Signal Processing,2015,9(4):691-701.
[8] SUN L J,CHEN X D,HAN C,et al.New Fuzzy-Clustering Algorithm for Data Stream[J].JEIT,2015,37(7):1620-1625.(in Chinese) 孙力娟,陈小东,韩崇,等.一种新的数据流模糊聚类方法[J].电子与信息学报,2015,37(7):1620-1625.
[9] FANG F,CHENG X J.A fast reduction method for massive scat-tered point cloud based on slicing[J].Geomatics and Information Science of Wuhan University,2013,38(11):1353-1357.(in Chinese) 方芳,程效军.海量散乱点云快速压缩算法[J].武汉大学学报(信息科学版),2013,8(11):1353-1357.
[10] BI A Q,DONG A M,WANG S T.A dynamic data stream clustering algorithm based on probability and exemplar[J].Journal of Computer Research and Development,2016,53(5):1029-1042.(in Chinese) 毕安琪,董爱美,王士同.基于概率和代表点的数据流动态聚类算法[J].计算机研究与发展,2016,53(5):1029-1042.
[11] JIANG Y Z,CHUNG F L,WANG S T,et al.Collaborative fuzzy clustering from multiple weighted views[J].IEEE Transactions on Cybernetics,2015,45(4):688-701.
[12] ZHANG J X,WANG S T,DENG Z H,et al.A subspace transfer learning algorithm integrating heterogeneous features[J].Acta Automatica Sinica,2014,40(2):236-246.(in Chinese) 张景祥,王士同,邓赵红,等.融合异构特征的子空间迁移学习算法[J].自动化学报,2014,40(2):236-246.
[13] XING C Z,LIU J.Evolutionary data stream clustering algorithm based on integration of affinity propagation and density[J].Journal of Computer Applications,2015,35(7):1927-1932.(in Chinese) 邢长征,刘剑.基于近邻传播与密度相融合的进化数据流聚类算法[J].计算机应用,2015,35(7):1927-1932.
[14] SONG X L,CHEN L,XIAO M.Verification scheme of retrievability supporting XOR rotated erasure codes for cloud storage data[J].Journal of Chongqing University of Posts and Telecommunication (Natural Science Edition),2012,4(6):682-686.(in Chinese) 宋秀丽,陈龙,肖敏.云存储中支持XOR旋转编码的可恢复性验证方案[J].重庆邮电大学学报(自然科学版),2012,4(6):682-686.

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