23 research outputs found
An Explicit Construction of Systematic MDS Codes with Small Sub-packetization for All-Node Repair
An explicit construction of systematic MDS codes, called HashTag+ codes, with
arbitrary sub-packetization level for all-node repair is proposed. It is shown
that even for small sub-packetization levels, HashTag+ codes achieve the
optimal MSR point for repair of any parity node, while the repair bandwidth for
a single systematic node depends on the sub-packetization level. Compared to
other codes in the literature, HashTag+ codes provide from 20% to 40% savings
in the average amount of data accessed and transferred during repair
A Family of Erasure Correcting Codes with Low Repair Bandwidth and Low Repair Complexity
We present the construction of a new family of erasure correcting codes for
distributed storage that yield low repair bandwidth and low repair complexity.
The construction is based on two classes of parity symbols. The primary goal of
the first class of symbols is to provide good erasure correcting capability,
while the second class facilitates node repair, reducing the repair bandwidth
and the repair complexity. We compare the proposed codes with other codes
proposed in the literature.Comment: Accepted, will appear in the proceedings of Globecom 2015 (Selected
Areas in Communications: Data Storage
A Repair Framework for Scalar MDS Codes
Several works have developed vector-linear maximum-distance separable (MDS)
storage codes that min- imize the total communication cost required to repair a
single coded symbol after an erasure, referred to as repair bandwidth (BW).
Vector codes allow communicating fewer sub-symbols per node, instead of the
entire content. This allows non trivial savings in repair BW. In sharp
contrast, classic codes, like Reed- Solomon (RS), used in current storage
systems, are deemed to suffer from naive repair, i.e. downloading the entire
stored message to repair one failed node. This mainly happens because they are
scalar-linear. In this work, we present a simple framework that treats scalar
codes as vector-linear. In some cases, this allows significant savings in
repair BW. We show that vectorized scalar codes exhibit properties that
simplify the design of repair schemes. Our framework can be seen as a finite
field analogue of real interference alignment. Using our simplified framework,
we design a scheme that we call clique-repair which provably identifies the
best linear repair strategy for any scalar 2-parity MDS code, under some
conditions on the sub-field chosen for vectorization. We specify optimal repair
schemes for specific (5,3)- and (6,4)-Reed- Solomon (RS) codes. Further, we
present a repair strategy for the RS code currently deployed in the Facebook
Analytics Hadoop cluster that leads to 20% of repair BW savings over naive
repair which is the repair scheme currently used for this code.Comment: 10 Pages; accepted to IEEE JSAC -Distributed Storage 201