English

Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction

Information Theory 2011-07-27 v2 Distributed, Parallel, and Cluster Computing Networking and Internet Architecture math.IT

Abstract

Regenerating codes are a class of distributed storage codes that optimally trade the bandwidth needed for repair of a failed node with the amount of data stored per node of the network. Minimum Storage Regenerating (MSR) codes minimize first, the amount of data stored per node, and then the repair bandwidth, while Minimum Bandwidth Regenerating (MBR) codes carry out the minimization in the reverse order. An [n, k, d] regenerating code permits the data to be recovered by connecting to any k of the n nodes in the network, while requiring that repair of a failed node be made possible by connecting (using links of lesser capacity) to any d nodes. Previous, explicit and general constructions of exact-regenerating codes have been confined to the case n=d+1. In this paper, we present optimal, explicit constructions of MBR codes for all feasible values of [n, k, d] and MSR codes for all [n, k, d >= 2k-2], using a product-matrix framework. The particular product-matrix nature of the constructions is shown to significantly simplify system operation. To the best of our knowledge, these are the first constructions of exact-regenerating codes that allow the number n of nodes in the distributed storage network, to be chosen independent of the other parameters. The paper also contains a simpler description, in the product-matrix framework, of a previously constructed MSR code in which the parameter d satisfies [n=d+1, k, d >= 2k-1].

Keywords

Cite

@article{arxiv.1005.4178,
  title  = {Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction},
  author = {K. V. Rashmi and Nihar B. Shah and P. Vijay Kumar},
  journal= {arXiv preprint arXiv:1005.4178},
  year   = {2011}
}

Comments

Submitted to IEEE Transactions on Information Theory. Contains 20 pages, 2 figures