ISCAS OpenIR
semi-random linear network coding for cloud storage redundancy
Xie Chui-Yi; Jia Zhong-Tian; Qing Si-Han; Luo Shou-Shan; Cheng Ming-Zhi
2013
SourceBeijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications
ISSN1007-5321
Volume36Issue:3Pages:30-34
English AbstractAccording to structural characteristics and availability requirements of cloud storage, a semi-random linear network coding (SRLNC) algorithm is proposed for data redundancy. The data block is split into pieces, encoded by coding matrix composed of unit row vectors and random row vectors on finite fields GF(2s), stored in data nodes dispersedly. In decoding process, the data block can be restored with the strategy of unit row vectors priority. The probability of unique solution is analyzed for SRLNC decoding equations, a new operations per character index is defined to measure algorithm efficiency. Experiments prove that the operating time of the decoding process in the proposed algorithm exponentially reduces with the increase of the node availability. When the availability of each node≥0.8 and redundancy&le3, the encoding operation of the proposed algorithm is faster up to 33%, and decoding operation of the proposed is 5 times faster than that of random linear network coding algorithm, respectively. It is shown that the proposed algorithm is applicable to "write once read many" cloud storage system.; According to structural characteristics and availability requirements of cloud storage, a semi-random linear network coding (SRLNC) algorithm is proposed for data redundancy. The data block is split into pieces, encoded by coding matrix composed of unit row vectors and random row vectors on finite fields GF(2s), stored in data nodes dispersedly. In decoding process, the data block can be restored with the strategy of unit row vectors priority. The probability of unique solution is analyzed for SRLNC decoding equations, a new operations per character index is defined to measure algorithm efficiency. Experiments prove that the operating time of the decoding process in the proposed algorithm exponentially reduces with the increase of the node availability. When the availability of each node≥0.8 and redundancy&le3, the encoding operation of the proposed algorithm is faster up to 33%, and decoding operation of the proposed is 5 times faster than that of random linear network coding algorithm, respectively. It is shown that the proposed algorithm is applicable to "write once read many" cloud storage system.
Indexed TypeEI
KeywordAlgorithms Decoding Linear Networks Network Coding Redundancy Vectors
Department(1) National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunications Beijing 100876 China; (2) School of Mathematics and Information Science Shaoguan University Guangdong Shaoguan 512005 China; (3) Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan 250022 China; (4) Institute of Software Chinese Academy of Sciences Beijing 100190 China; (5) Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China; (6) College of Information Engineering Beijing Institute of Graphic Communication Beijing 102600 China
Language中文
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/15670
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Xie Chui-Yi,Jia Zhong-Tian,Qing Si-Han,et al. semi-random linear network coding for cloud storage redundancy[J]. Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications,2013,36(3):30-34.
APA Xie Chui-Yi,Jia Zhong-Tian,Qing Si-Han,Luo Shou-Shan,&Cheng Ming-Zhi.(2013).semi-random linear network coding for cloud storage redundancy.Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications,36(3),30-34.
MLA Xie Chui-Yi,et al."semi-random linear network coding for cloud storage redundancy".Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications 36.3(2013):30-34.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xie Chui-Yi]'s Articles
[Jia Zhong-Tian]'s Articles
[Qing Si-Han]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xie Chui-Yi]'s Articles
[Jia Zhong-Tian]'s Articles
[Qing Si-Han]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xie Chui-Yi]'s Articles
[Jia Zhong-Tian]'s Articles
[Qing Si-Han]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.