2006Unpublished venueRequires access

Optimizing Cauchy Reed-Solomon Codes for Fault-Tolerant Network Storage Applications

Lihao Xu James S. Plank

Open publisher page 238 citations

Abstract

In the past few years, all manner of storage applications, ranging from disk array systems to distributed and wide-area systems, have started to grapple with the reality of tolerating multiple simultaneous failures of storage nodes. Unlike the single failure case, which is optimally handled with RAID Level-5 parity, the multiple failure case is more difficult because optimal general purpose strategies are not yet known. Erasure Coding is the field of research that deals with these strategies, and this field has blossomed in recent years. Despite this research, the decades-old Reed- Solomon erasure code remains the only space-optimal (MDS) code for all but the smallest storage systems. The best performing implementations of Reed-Solomon coding employ a variant called Cauchy Reed-Solomon coding, developed in the mid 1990’s [4]. In this paper, we present an improvement to Cauchy Reed-Solomon coding that is based on optimizing the Cauchy distribution matrix. We detail an algorithm for generating good matrices and then evaluate the performance of encoding using all implementations Reed- Solomon codes, plus the best MDS codes from the literature. The improvements over the original Cauchy Reed-Solomon codes are as much as 83% in realistic scenarios, and average roughly 10% over all cases that we tested.

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What this paper is about

In the past few years, all manner of storage applications, ranging from disk array systems to distributed and wide-area systems, have started to grapple with the reality of tolerating multiple simultaneous failures of storage nodes. Unlike the single failure case, which is optimally handled with RAID Level-5 parity, the multiple failure case is more difficult because optimal general purpose strategies are not yet known. Erasure Coding is the field of research that deals with these strategies, and this field has blossomed in recent years. Despite this research, the decades-old Reed- Solomon erasure code remains the only space-optimal (MDS) code for all but the smallest storage systems. The best performing implementations of Reed-Solomon coding employ a variant called Cauchy Reed-Solomon coding, developed in the mid 1990’s [4]. In this paper, we present an improvement to Cauchy Reed-Solomon coding that is based on optimizing the Cauchy distribution matrix. We detail an algorithm for generating good matrices and then evaluate the performance of encoding using all implementations Reed- Solomon codes, plus the best MDS codes from the literature. The improvements over the original Cauchy Reed-Solomon codes are as much as 83% in realistic scenarios, and average roughly 10% over all cases that we tested.

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OpenAlex reports 238 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In the past few years, all manner of storage applications, ranging from disk array systems to distributed and wide-area systems, have started to grapple with the reality of tolerating multiple simultaneous failures of storage nodes. Unlike the single failure case, which is optimally handled with RAID Level-5 parity, the multiple failure case is more difficult because optimal general purpose strategies are not yet known. Erasure Coding is the field of research that deals with these strategies, and this field has blossomed in recent years. Despite this research, the decades-old Reed- Solomon erasure code remains the only space-optimal (MDS) code for all but the smallest storage systems. The best performing implementations of Reed-Solomon coding employ a variant called Cauchy Reed-Solomon coding, developed in the mid 1990’s [4]. In this paper, we present an improvement to Cauchy Reed-Solomon coding that is based on optimizing the Cauchy distribution matrix. We detail an algorithm for generating good matrices and then evaluate the performance of encoding using all implementations Reed- Solomon codes, plus the best MDS codes from the literature. The improvements over the original Cauchy Reed-Solomon codes are as much as 83% in realistic scenarios, and average roughly 10% over all cases that we tested.

Key concepts: Computer science, Reed–Solomon error correction, Fault tolerance, Parallel computing, Concatenated error correction code, Telecommunications, Decoding methods, Distributed computing

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