1,193 research outputs found
Optimal Locally Repairable Codes and Connections to Matroid Theory
Petabyte-scale distributed storage systems are currently transitioning to
erasure codes to achieve higher storage efficiency. Classical codes like
Reed-Solomon are highly sub-optimal for distributed environments due to their
high overhead in single-failure events. Locally Repairable Codes (LRCs) form a
new family of codes that are repair efficient. In particular, LRCs minimize the
number of nodes participating in single node repairs during which they generate
small network traffic. Two large-scale distributed storage systems have already
implemented different types of LRCs: Windows Azure Storage and the Hadoop
Distributed File System RAID used by Facebook. The fundamental bounds for LRCs,
namely the best possible distance for a given code locality, were recently
discovered, but few explicit constructions exist. In this work, we present an
explicit and optimal LRCs that are simple to construct. Our construction is
based on grouping Reed-Solomon (RS) coded symbols to obtain RS coded symbols
over a larger finite field. We then partition these RS symbols in small groups,
and re-encode them using a simple local code that offers low repair locality.
For the analysis of the optimality of the code, we derive a new result on the
matroid represented by the code generator matrix.Comment: Submitted for publication, a shorter version was presented at ISIT
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