An @math -vector MDS code is a @math -linear subspace of @math (for some field @math ) of dimension @math , such that any @math (vector) symbols of the codeword suffice to determine the remaining @math (vector) symbols. The length @math of each codeword symbol is called the sub-packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading @math field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large sub-packetization @math . Our main result is an almost tight lower bound showing that for an MSR code, one must have @math . Previously, a lower bound of @math , and a tight lower bound for a restricted class of "optimal access" MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one key definition that is somewhat inspired by Galois theory.
We begin code constructions existence results. present an explicit construction of MSR codes with small sub-packetization @math when the code rate @math is at most @math @cite_1 . @cite_5 show the existence of high rate MSR codes when the sub-packetization approaches infinity. Motivated by this result, the problem of designing high-rate MSR codes with finite sub-packetization level is explored in @cite_11 @cite_27 @cite_26 @cite_23 @cite_14 @cite_28 @cite_2 @cite_13 @cite_4 and references therein. In particular, @cite_16 show the existence of MSR codes with the sub-packetization level @math . Such a result with similar sub-packetization levels for repair of only @math systematic nodes was obtained earlier in @cite_15 @cite_14 . In order to ensure the MDS property, these results relied on huge fields and randomized construction of the parity check matrices.
@cite_26 @cite_14 @cite_4 @cite_28 @cite_1 @cite_27 @cite_23 @cite_2 @cite_5 @cite_15 @cite_16 @cite_13 @cite_11
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We present a high-rate @math -MSR code with a sub-packetization level that is polynomial in the dimension @math of the code. While polynomial sub-packetization level was achieved earlier for vector MDS codes that repair systematic nodes optimally, no such MSR code construction is known. In the low-rate regime (i. e., rates less than one-half), MSR code constructions with a linear sub-packetization level are available. But in the high-rate regime (i. e., rates greater than one-half), the known MSR code constructions required a sub-packetization level that is exponential in @math . In the present paper, we construct an MSR code for @math with a fixed rate @math achieveing a sub-packetization level @math . The code allows help-by-transfer repair, i. e., no computations are needed at the helper nodes during repair of a failed node. We present a high-rate (n, k, d = n − 1)-MSR code with a sub-packetization level that is polynomial in the dimension k of the code. While polynomial sub-packetization level was achieved earlier for vector MDS codes that repair systematic nodes optimally, no such MSR code construction is known. In the low-rate regime (i. e., rates less than one-half), MSR code constructions with a linear sub-packetization level are available. But in the high-rate regime (i. e., rates greater than one-half), the known MSR code constructions required a sub-packetization level that is exponential in k. In the present paper, we construct an MSR code for d = n − 1 with a fixed rate equation, achieveing a sub-packetization level α = O(kt). The code allows help-by-transfer repair, i. e., no computations are needed at the helper nodes during repair of a failed node. This paper presents an explicit construction for an @math regenerating code over a field @math operating at the Minimum Storage Regeneration (MSR) point. The MSR code can be constructed to have rate @math as close to @math as desired, sub-packetization given by @math , for @math , field size no larger than @math and where all code symbols can be repaired with the same minimum data download. The construction modifies a prior construction by Sasidharan et. al. which required far larger field-size. A building block appearing in the construction is a scalar MDS code of block length @math . The code has a simple layered structure with coupling across layers, that allows both node repair and data recovery to be carried out by making multiple calls to a decoder for the scalar MDS code. While this work was carried out independently, there is considerable overlap with a prior construction by Ye and Barg. It is shown here that essentially the same architecture can be employed to construct MSR codes using vector binary MDS codes as building blocks in place of scalar MDS codes. The advantage here is that computations can now be carried out over a field of smaller size potentially even over the binary field as we demonstrate in an example. Further, we show how the construction can be extended to handle the case of @math under a mild restriction on the choice of helper nodes. The first focus of the present paper, is on lower bounds on the sub-packetization level @math of an MSR code that is capable of carrying out repair in help-by-transfer fashion (also called optimal-access property). We prove here a lower bound on @math which is shown to be tight for the case @math by comparing with recent code constructions in the literature. We also extend our results to an @math MDS code over the vector alphabet. Our objective even here, is on lower bounds on the sub-packetization level @math of an MDS code that can carry out repair of any node in a subset of @math nodes, @math where each node is repaired (linear repair) by help-by-transfer with minimum repair bandwidth. We prove a lower bound on @math for the case of @math . This bound holds for any @math and is shown to be tight, again by comparing with recent code constructions in the literature. Also provided, are bounds for the case @math . We study the form of a vector MDS code having the property that we can repair failed nodes belonging to a fixed set of @math nodes with minimum repair bandwidth and in optimal-access fashion, and which achieve our lower bound on sub-packetization level @math . It turns out interestingly, that such a code must necessarily have a coupled-layer structure, similar to that of the Ye-Barg code. The first focus of the present paper, is on lower bounds on the sub-packetization level @math of an MSR code that is capable of carrying out repair in help-by-transfer fashion (also called optimal-access property). We prove here a lower bound on @math which is shown to be tight for the case @math by comparing with recent code constructions in the literature. We also extend our results to an @math MDS code over the vector alphabet. Our objective even here, is on lower bounds on the sub-packetization level @math of an MDS code that can carry out repair of any node in a subset of @math nodes, @math where each node is repaired (linear repair) by help-by-transfer with minimum repair bandwidth. We prove a lower bound on @math for the case of @math . This bound holds for any @math and is shown to be tight, again by comparing with recent code constructions in the literature. Also provided, are bounds for the case @math Q @math $ . It turns out interestingly, that such a code must necessarily have a coupled-layer structure, similar to that of the Ye-Barg code. Given any r and n, we present an explicit construction of high-rate maximum distance separable (MDS) array codes that can optimally repair any d failed nodes from any h helper nodes for all h, 1 ≤ h ≤ r and d, k ≤ d ≤ n − h simultaneously. These codes can be constructed over any base field F as long as |F| ≥ sn; where s = lcm(1, 2, …, r). The encoding, decoding, repair of failed nodes, and update procedures of these codes all have low complexity. Our results present a significant improvement over earlier results which can only construct explicit codes for the case of at most 3 parity nodes, and these existing constructions can only optimally repair a single node failure by accessing all the surviving nodes. In the second part of the paper we give an explicit construction of Reed-Solomon codes with asymptotically optimal repair bandwidth. This paper presents a construction for high-rate MDS codes that enable bandwidth-efficient repair of a single node. Such MDS codes are also referred to as the minimum storage regenerating (MSR) codes in the distributed storage literature. The construction presented in this paper generates MSR codes for all possible number of helper nodes d as d is a design parameter in the construction. Furthermore, the obtained MSR codes have polynomial sub-packetization (a.k.a. node size) α. The construction is built on the recent code proposed by [1], which works only for d = n — 1, i.e., where all the remaining nodes serve as the helper nodes for the bandwidth-efficient repair of a single node. The results of this paper broaden the set of parameters where the constructions of MSR codes were known earlier. An (n, k, l) MDS code of length n, dimension k and sub-packetization l over a finite field F is a set of n symbol vectors of length l over F with the property that any k vector can recover the entire data of kl symbols. When a node fails we can recover it by downloading symbols from the surviving nodes, and the total number of symbols downloaded in th worst case is the repair bandwidth of the code. By the cut-se bound, the repair bandwidth of an (n, k, l) MDS code is at leas (n − 1)l (n − k). There are several constructions of (n, k, l) MDS codes whose repair bandwidths meet or asymptotically meet the cut-se bound. Letting r = n − k denote the number of parities Ye and Barg constructed (n, k, rn) Reed-Solomon codes the asymptotically meet the cut-set bound. Ye and Barg also constructed optimal bandwidth and optimal update (n, k, rn MDS codes. A key idea in these constructions is to expand integers in base r. We show in this paper that, when r is an integral power, w can significantly reduce the sub-packetization of the Ye-Barg constructions while achieving asymptotically optimal repair bandwidth. As an example, when r = 2m, we achieve the sub-packetization of 2m+n−1, which improves upon the sub packetization of 2mn in the Ye-Barg constructions. In general when r = sm for an integer s  2, our codes have sub packetization l = sm+n−1 = rsn−1. Specifically, in the casi r = sm, we obtain an (n, k, sm+n=1) Reed-Solomon code an an optimal update (n, k, sm+n−1) MDS code, which both have asymptotically optimal repair bandwidth. In order to obtain these results, we extend and generalize the r-ary expansion idea in the Ye-Barg constructions. Even when r is not an integral power, we can still obtain (n, k, sm+n−1) Reed-Solomon codes and optimal update (n, k, sm+n−1) MDS codes by choosing positive integers s an m such that sm  r. In this case, however, the resulting codes have bandwidth that is near-optimal rather than asymptotically optimal. An @math maximum distance separable (MDS) array code of length @math , dimension @math , and sub-packetization @math is formed of @math matrices over a finite field @math , with every column of the matrix stored on a separate node in the distributed storage system and viewed as a coordinate of the codeword. Repair of a failed node (recovery of one erased column) can be performed by accessing a set of @math surviving (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 @math , the sub-packetization @math satisfies the bound @math . In our previous work (IEEE Trans. Inf. Theory, vol. 63, no. 4, 2017), for any @math and @math , we presented an explicit construction of optimal-access MDS codes with sub-packetization @math . In this paper, we take up the question of reducing the sub-packetization value @math to make it to approach the lower bound. We construct an explicit family of optimal-access codes with @math , which differs from the optimal value by at most a factor of @math . These codes can be constructed over any finite field @math as long as @math , 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), which we call group repair with optimal access . In this variation, we assume that the set of @math nodes is partitioned into @math repair groups of size @math , and require that the amount of accessed data for repair is the smallest possible whenever the @math helper nodes include all the other @math 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 @math of size @math , and also afford low-complexity encoding and decoding procedures. The repair problem for an (n, k) error-correcting code calls for recovery of an unavailable coordinate of the codeword by downloading as little information as possible from a subset of the remaining coordinates. Using the terminology motivated by coding in distributed storage, we attempt to repair a failed node by accessing information stored on d helper nodes, where k &#x227C; d &#x227C; n &#x2013; 1, and using as little repair bandwidth as possible to recover the lost information.By the so-called cut-set bound (, 2010), the repair bandwidth of an (n,k = n &#x2013; r) MDS code using d helper nodes is at least dl (d + 1 &#x2013; k), where l is the size of the node. A number of constructions of MDS array codes have been shown to meet this bound with equality. In a related but separate line of work, Guruswami and Wootters (2016) studied repair of Reed-Solomon (RS) codes, showing that it is possible to perform repair using a smaller bandwidth than under the trivial approach. At the same time, their work as well as follow-up papers stopped short of constructing RS codes (or any scalar MDS codes) that meet the cut-set bound with equality, which has been an open problem in coding theory.In this work we present a solution to this problem, constructing RS codes of length n over the field of size (ql, l = exp((1 + o(1)n log n) that meet the cut-set bound. We also prove an almost matching lower bound on l, showing that super-exponential scaling is both necessary and sufficient for achieving the cut-set bound using linear repair schemes. More precisely, we prove that for scalar MDS codes (including the RS codes) to meet this bound, the sub-packetization l must satisfy l &#x227D; exp((1 + o(1))k log k). Maximum distance separable (MDS) codes are optimal error-correcting codes in the sense that they provide the maximum failure tolerance for a given number of parity nodes. Suppose that an MDS code with @math information nodes and @math parity nodes is used to encode data in a distributed storage system. It is known that if @math out of the @math nodes are inaccessible and @math surviving (helper) nodes are used to recover the lost data, then we need to download at least @math fraction of the data stored in each of the helper nodes ( , 2010 and , 2013). If this lower bound is achieved for the repair of any @math erased nodes from any @math helper nodes, we say that the MDS code has the @math -optimal repair property. We study high-rate MDS array codes with the optimal repair property (also known as minimum storage regenerating codes, or MSR codes). Explicit constructions of such codes in the literature are only available for the cases where there are at most three parity nodes, and these existing constructions can only optimally repair a single node failure by accessing all the surviving nodes. In this paper, given any @math and @math , we present two explicit constructions of MDS array codes with the @math -optimal repair property for all @math and @math simultaneously. Codes in the first family can be constructed over any base field @math as long as @math , where @math . The encoding, decoding, repair of failed nodes, and update procedures of these codes all have low complexity. Codes in the second family have the optimal access property and can be constructed over any base field @math as long as @math . Moreover, both code families have the optimal error resilience capability when repairing failed nodes. We also construct several other related families of MDS codes with the optimal repair property. This paper addresses the problem of constructing maximum distance separable (MDS) codes that enable exact reconstruction (repair) of each code block by downloading a small amount of information from the remaining code blocks. The total amount of information flow from the remaining code blocks during this reconstruction process is referred to as repair bandwidth of the underlying code. Existing constructions of exact-repairable MDS codes with optimal repair bandwidth require working with large subpacketization levels, which restrict their applicability in practice. This paper presents two general approaches to construct exact-repairable MDS codes that aim at significantly reducing the required subpacketization level at the cost of slightly suboptimal repair bandwidth. The first approach provides MDS codes that have repair bandwidth at most twice the optimal repair bandwidth. In addition, these codes also have the smallest possible subpacketization level @math , where @math denotes the number of parity blocks. This approach is then generalized to design codes that have their repair bandwidth approaching the optimal repair bandwidth at the cost of graceful increment in the required subpacketization level. The second approach transforms an MDS code with optimal repair bandwidth and large subpacketization level into a longer MDS code with small subpacketization level and near-optimal repair bandwidth. For a given @math , the codes constructed using this approach have their subpacketization level scaling logarithmically with the code length. In addition, the obtained codes require field size only linear in the code length and ensure load balancing among the intact code blocks in terms of the information downloaded from these blocks during the exact reconstruction of a code block. Let F sub q denote the finite field GF(q) and let h be a positive integer. MDS (maximum distance separable) codes over the symbol alphabet F sub q sup b are considered that are linear over F sub q and have sparse ("low-density") parity-check and generator matrices over F sub q that are systematic over F sub q sup b . Lower bounds are presented on the number of nonzero elements in any systematic parity-check or generator matrix of an F sub q -linear MDS code over F sub q sup b , along with upper bounds on the length of any MDS code that attains those lower bounds. A construction is presented that achieves those bounds for certain redundancy values. The building block of the construction is a set of sparse nonsingular matrices over F sub q whose pairwise differences are also nonsingular. Bounds and constructions are presented also for the case where the systematic condition on the parity-check and generator matrices is relaxed to be over F sub q , rather than over F sub q sup b .