标题:Improved constructions for optimal multi-erasure locally recoverable codes for big data storage
作者:Qian, Jianfa ;Zhang, Lina
作者机构:[Qian, Jianfa ;Zhang, Lina ] School of Mathematics and Big Data, Huizhou University, Huizhou, Guangdong; 516007, China
会议名称:2nd International Conference on Big Data Technologies, ICBDT 2019
会议日期:August 28, 2019 - August 30, 2019
来源:ACM International Conference Proceeding Series
出版年:2019
页码:44-47
DOI:10.1145/3358528.3358581
摘要:Multi-erasure locally recoverable codes play a very significant role in distributed data storage. The advantage of multi-erasure locally recoverable codes is that it has local and global erasure-correcting characteristics. Recently, based on classical algebraic geometry codes, Huang et al. constructed a family of explicit optimal multi-erasure locally recoverable codes over small finite fields F4 . In this work, based on the work of Huang et al., we use cyclic codes to construct a family of new optimal multi-erasure locally recoverable codes over small finite fields F3 . It turns out that our multi-erasure locally recoverable codes have smaller finite fields than the previously known results.
© 2019 Association for Computing Machinery.
收录类别:EI
资源类型:会议论文
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