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  • 标题:Improving the Efficiency of Deduplication Process by Dedicated Hash Table for each Digital Data Type in Cloud Storage System
  • 本地全文:下载
  • 作者:G. Sujatha ; Jeberson Retna Raj
  • 期刊名称:Webology
  • 印刷版ISSN:1735-188X
  • 出版年度:2021
  • 卷号:18
  • 期号:Special Issue 01
  • 页码:288-301
  • DOI:10.14704/WEB/V18SI01/WEB18060
  • 出版社:University of Tehran
  • 摘要:Data storage is one of the significant cloud services available to the cloud users. Since the magnitude of information outsourced grows extremely high, there is a need of implementing data deduplication technique in the cloud storage space for efficient utilization. The cloud storage space supports all kind of digital data like text, audio, video and image. In the hash-based deduplication system, cryptographic hash value should be calculated for all data irrespective of its type and stored in the memory for future reference. Using these hash value only, duplicate copies can be identified. The problem in this existing scenario is size of the hash table. To find a duplicate copy, all the hash values should be checked in the worst case irrespective of its data type. At the same time, all kind of digital data does not suit with same structure of hash table. In this study we proposed an approach to have multiple hash tables for different digital data. By having dedicated hash table for each digital data type will improve the searching time of duplicate data.
  • 其他摘要:Data storage is one of the significant cloud services available to the cloud users. Since the magnitude of information outsourced grows extremely high, there is a need of implementing data deduplication technique in the cloud storage space for efficient utilization. The cloud storage space supports all kind of digital data like text, audio, video and image. In the hash-based deduplication system, cryptographic hash value should be calculated for all data irrespective of its type and stored in the memory for future reference. Using these hash value only, duplicate copies can be identified. The problem in this existing scenario is size of the hash table. To find a duplicate copy, all the hash values should be checked in the worst case irrespective of its data type. At the same time, all kind of digital data does not suit with same structure of hash table. In this study we proposed an approach to have multiple hash tables for different digital data. By having dedicated hash table for each digital data type will improve the searching time of duplicate data.
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