Heuristics for Optimizing Matrix-Based Erasure Codes for Fault-Tolerant Storage Systems

James S. Plank, EECS Department, University of Tennessee.
Catherine D. Schuman, EECS Department, University of Tennessee.
B. Devin Robison, School of Computing, University of Utah.

Appearing in DSN-2012: The 42nd Annual IEEE/IFIP Internaltional Conference on Dependable Systems and Networks, Boston, MA, June, 2012.

PDF of the accepted submission. When I get a link, I'll point you to the final IEEE version on their web site.

Open Source Software of the Algorithms


Large scale, archival and wide-area storage systems use erasure codes to protect users from losing data due to the inevitable failures that occur. All but the most basic erasure codes employ bit-matrices so that encoding and decoding may be effected solely with the bitwise exclusive-OR (XOR) operation. There are CPU savings that can result from strategically scheduling these XOR operations so that fewer XOR's are performed. It is an open problem to derive a schedule from a bit-matrix that minimizes the number of XOR operations.

We attack this open problem, deriving two new heuristics called Uber-CHRS and X-Sets to schedule encoding and decoding bit-matrices with reduced XOR operations. We evaluate these heuristics in a variety of realistic erasure coding settings and demonstrate that they are a significant improvement over previously published heuristics. We provide an open-source implementation of these heuristics so that practitioners may leverage our work.

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