CCRS: An Optimized Algorithm Based on CRS in Distributed Storage System

It is well-known that erasure codes, such as Reed-Solomn (RS) and Cauchy Reed-Solumn Codes (CRS), have played an important roles in distributed storage system to both industry and academic. While RS and CRS codes provide significant savings in storage space, they will decrease systems performance while encoding and decoding. In this paper we have developed an optimized algorithm named CCRS (Changed CRS) based on erasure coding technology, which can not only protect the system's reliability, but also improve the utilization of storage space. By studying existing high reliability and space saving rate of coding technology, we imported coding mechanism into distributed storage systems. Theory analysis and simulation test show CCRS algorithm can improve the performance. CCRS algorithm can reduce the number of XOR in Galois field so that we can conclude that CCRS can shorten the time of encoding and decoding. The simulation test results shows that parallel decoding speed can rise up nearly two times than the past serial decoding speed. The encoding efficiency with CCRS coding is 36.1% and 58.2% higher than using CRS and RS coding equally. The decoding rate by using CCRS is 19.3% and 33.1% higher than using CRS and RS averagely.