Journal article

Improved upper bounds on systematic-length for linear minimum storage regenerating codes

K Huang, U Parampalli, M Xian

IEEE Transactions on Information Theory | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2019

Abstract

In this paper, we revisit the problem of finding the longest systematic-length k for a linear minimum storage regenerating (MSR) code with optimal repair of only systematic part, for a given per-node storage capacity l and an arbitrary number of parity nodes r. We study the problem by following a geometric analysis of linear subspaces and operators. First, a simple quadratic bound is given, which implies that k=r+2 is the largest number of systematic nodes in the scalar scenario. Second, an r-based-log bound is derived, which is superior to the upper bound on log-base 2 in the prior work. Finally, an explicit upper bound depending on the value of r2/l is introduced, which further extends the..

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University of Melbourne Researchers