Second Order Mutual Information based Grey Wolf Optimization for effective storage and de-duplication

作     者：Malhotra, Jyoti Bakal, Jagdish 

作者机构：RTM Univ Nagpur GH Raisoni Coll Engn Dept Comp Sci & Engn Nagpur 440016 Maharashtra India 

出 版 物：《SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES》 (Sadhana)

年 卷 期：2018年第43卷第11期

页      面：185-185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] 

主　　题：De-duplication simhash algorithm Huffman coding Grey Wolf Optimization accuracy 

摘      要：This paper intends to perform de-duplication for enhancing the storage optimization by utilizing the similarity in mutual information. Hence, this paper contributes by proposing a hybrid fingerprint extracting using SH and HC algorithms. Secondly, the data is clustered using the latest technique called as SOMI-GO to extract the metadata. The extracted metadata is stored in metadata server which provides better storage optimization and de-duplication. SOMI-GO is adopted as it provides maximum second-order mutual information based on the similarity index. The proposed SOMI-GO technique is compared with the existing methods such as K-means, K-mode, ED-PSO, ED-GA and ED-GWO in terms of accuracy, TPR, TNR and performance time and the significance of the SOMI-GO method is described.