Optimizing the Parity Check Matrix for Efficient Decoding of RS-Based Cloud Storage Systems

In large scale distributed systems such as cloud storage systems, erasure coding is a fundamental technique to provide high reliability at low monetary cost. Compared with the traditional disk arrays, cloud storage systems use an erasure coding scheme with both flexible fault tolerance and high scalability. Thus, Reed-Solomon (RS) Codes or RS-based codes are popular choices for cloud storage systems. However, the decoding performance for RS-based codes is not as good as XOR-based codes, which are optimized via investigating the relationships among different parity chains or reducing the computational complexity of matrix multiplications. Therefore, exploring an efficient decoding method is highly desired. To address the above problem, in this paper, we propose an Advanced Parity-Check Matrix (APCM) based approach, which is extended from the original Parity-Check Matrix based (PCM) approach. Instead of improving the decoding performance of XOR-based codes in PCM, APCM focuses on optimizing the decoding efficiency for RS-based codes. Furthermore, APCM avoids the matrix inversion computations and reduces the computational complexity of the decoding process. To demonstrate the effectiveness of the APCM, we conduct intensive experiments by using both RS-based and XOR-based codes under cloud storage environment. The results show that, compared to typical decoding methods, APCM improves the decoding speed by up to 32.31% in the Alibaba cloud storage system.