Improved Constructions for Optimal Multi-erasure Locally Recoverable Codes for Big Data Storage
Jianfa Qian, Lina Zhang
Abstract
Jianfa Qian, Lina Zhang
Abstract
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.
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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.
Key concepts: Erasure, Erasure code, Online codes, Construct (python library), Computer science, Finite field, Tornado code, Storage efficiency