Optimal storage codes on graphs with fixed locality
Sabyasachi Basu, Manuj Mukherjee

TL;DR
This paper characterizes the maximum rate of binary storage codes on graphs with fixed locality, establishing bounds and demonstrating an asymptotic separation based on locality growth.
Contribution
It provides explicit bounds on the rate of storage codes with fixed locality and constructs graphs achieving these bounds, extending understanding of local repairability in distributed storage.
Findings
Maximum rate bounds for codes with locality r are tight.
Explicit graph constructions achieve the lower bound on rate.
Asymptotic results relate code rate to locality growth.
Abstract
Storage codes on graphs are an instance of \emph{codes with locality}, which are used in distributed storage schemes to provide local repairability. Specifically, the nodes of the graph correspond to storage servers, and the neighbourhood of each server constitute the set of servers it can query to repair its stored data in the event of a failure. A storage code on a graph with -vertices is a set of -length codewords over where the th codeword symbol is stored in server , and it can be recovered by querying the neighbours of server according to the underlying graph. In this work, we look at binary storage codes whose repair function is the parity check, and characterise the tradeoff between the locality of the code and its rate. Specifically, we show that the maximum rate of a code on vertices with locality is bounded between $1-1/n\lceil…
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Taxonomy
TopicsCaching and Content Delivery · Advanced Data Storage Technologies · Cooperative Communication and Network Coding
