Emergent Mind

Abstract

An $(n,k,l)$ MDS array code of length $n,$ dimension $k=n-r$ and sub-packetization $l$ is formed of $l\times n$ matrices over a finite field $F,$ with every column of the matrix stored on a separate node in a distributed storage system and viewed as a coordinate of the codeword. Repair of a failed node can be performed by accessing a set of $d\le n-1$ helper nodes. The code is said to have the optimal access property if the amount of data accessed at each of the helper nodes meets a lower bound on this quantity. For optimal-access MDS codes with $d=n-1,$ the sub-packetization $l$ satisfies the bound $l\ge r{(k-1)/r}.$ In our previous work, for any $n$ and $r,$ we presented an explicit construction of optimal-access MDS codes with sub-packetization $l=r{n-1}.$ In this paper we take up the question of reducing the sub-packetization value $l$ to make it approach the lower bound. We construct an explicit family of optimal-access codes with $l=r{\lceil n/r\rceil},$ which differs from the optimal value by at most a factor of $r2.$ These codes can be constructed over any finite field $F$ as long as $|F|\ge r\lceil n/r\rceil,$ and afford low-complexity encoding and decoding procedures. We also define a version of the repair problem that bridges the context of regenerating codes and codes with locality constraints (LRC codes), calling it group repair with optimal access. In this variation, we assume that the set of $n=sm$ nodes is partitioned into $m$ repair groups of size $s,$ and require that the amount of accessed data for repair is the smallest possible whenever the $d$ helper nodes include all the other $s-1$ nodes from the same group as the failed node. For this problem, we construct a family of codes with the group optimal access property. These codes can be constructed over any field $F$ of size $|F|\ge n,$ and also afford low-complexity encoding and decoding procedures.

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