Cyclic Structure in Regenerating Codes

2014 ◽  
Vol 539 ◽  
pp. 416-419
Author(s):  
Wen Juan Liang ◽  
Ying Du
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Erasure Codes ◽  
Cyclic Structure ◽  
Distributed Storage Systems ◽  
Regenerating Codes ◽  
Original Message

Regenerating codes are a class of erasure codes for distributed storage. The use of regenerating codes not only improves reliability of distributed storage systems, but also minimizes repairing bandwidth when storage nodes failed and need to be repaired. In this paper, we investigate the cyclic structure of hybrid regenerating codes which each node has two fragments with the first fragment stores original message and the second fragment stores parity message. A fast repairing algorithm is also proposed.

Tree-Structured Parallel Regeneration Based on Regenerating Codes for Multiple Data Losses in Distributed Storage Systems

2014 ◽  
Vol 918 ◽  
pp. 295-300
Author(s):  
Peng Fei You ◽  
Yu Xing Peng ◽  
Zhen Huang ◽  
Chang Jian Wang
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Data Loss ◽  
Data Reliability ◽  
Data Redundancy ◽  
Regeneration Time ◽  
Multiple Data ◽  
Distributed Storage Systems ◽  
Regenerating Codes ◽  
Reliability And Availability

In distributed storage systems, erasure codes represent an attractive data redundancy solution which can provide the same reliability as replication requiring much less storage space. Multiple data losses happens usually and the lost data should be regenerated to maintain data redundancy in distributed storage systems. Regeneration for multiple data losses is expected to be finished as soon as possible, because the regeneration time can influence the data reliability and availability of distributed storage systems. However, multiple data losses is usually regenerated by regenerating single data loss one by one, which brings high entire regeneration time and severely reduces the data reliability and availability of distributed storage systems. In this paper, we propose a tree-structured parallel regeneration scheme based on regenerating codes (TPRORC) for multiple data losses in distributed storage systems. In our scheme, multiple regeneration trees based on regenerating code are constructed. Firstly, these trees are created independently, each of which dose not share any edges from the others and is responsible for one data loss; secondly, every regeneration tree based on regenerating codes owns the least network traffic and bandwidth optimized-paths for regenerating its data loss. Thus it can perform parallel regeneration for multiple data losses by using multiple optimized topology trees, in which network bandwidth is utilized efficiently and entire regeneration is overlapped. Our simulation results show that the tree-structured parallel regeneration scheme reduces the regeneration time significantly, compared to other regular regeneration schemes.

AN EXPLORATION OF NON-ASYMPTOTIC LOW-DENSITY, PARITY CHECK ERASURE CODES FOR WIDE-AREA STORAGE APPLICATIONS

2007 ◽  
Vol 17 (01) ◽  
pp. 103-123 ◽  
Author(s):  
JAMES S. PLANK ◽  
MICHAEL G. THOMASON
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Ldpc Codes ◽  
Peer To Peer ◽  
Erasure Codes ◽  
Low Density ◽  
Parity Check ◽  
Finite Systems ◽  
Low Density Parity Check ◽  
Distributed Storage Systems

As peer-to-peer and widely distributed storage systems proliferate, the need to perform efficient erasure coding, instead of replication, is crucial to performance and efficiency. Low-Density Parity-Check (LDPC) codes have arisen as alternatives to standard erasure codes, such as Reed-Solomon codes, trading off vastly improved decoding performance for inefficiencies in the amount of data that must be acquired to perform decoding. The scores of papers written on LDPC codes typically analyze their collective and asymptotic behavior. Unfortunately, their practical application requires the generation and analysis of individual codes for finite systems. This paper attempts to illuminate the practical considerations of LDPC codes for peer-to-peer and distributed storage systems. The three main types of LDPC codes are detailed, and a huge variety of codes are generated, then analyzed using simulation. This analysis focuses on the performance of individual codes for finite systems, and addresses several important heretofore unanswered questions about employing LDPC codes in real-world systems.

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