994 research outputs found
Repairable Block Failure Resilient Codes
In large scale distributed storage systems (DSS) deployed in cloud computing,
correlated failures resulting in simultaneous failure (or, unavailability) of
blocks of nodes are common. In such scenarios, the stored data or a content of
a failed node can only be reconstructed from the available live nodes belonging
to available blocks. To analyze the resilience of the system against such block
failures, this work introduces the framework of Block Failure Resilient (BFR)
codes, wherein the data (e.g., file in DSS) can be decoded by reading out from
a same number of codeword symbols (nodes) from each available blocks of the
underlying codeword. Further, repairable BFR codes are introduced, wherein any
codeword symbol in a failed block can be repaired by contacting to remaining
blocks in the system. Motivated from regenerating codes, file size bounds for
repairable BFR codes are derived, trade-off between per node storage and repair
bandwidth is analyzed, and BFR-MSR and BFR-MBR points are derived. Explicit
codes achieving these two operating points for a wide set of parameters are
constructed by utilizing combinatorial designs, wherein the codewords of the
underlying outer codes are distributed to BFR codeword symbols according to
projective planes
Coding with Constraints: Minimum Distance Bounds and Systematic Constructions
We examine an error-correcting coding framework in which each coded symbol is
constrained to be a function of a fixed subset of the message symbols. With an
eye toward distributed storage applications, we seek to design systematic codes
with good minimum distance that can be decoded efficiently. On this note, we
provide theoretical bounds on the minimum distance of such a code based on the
coded symbol constraints. We refine these bounds in the case where we demand a
systematic linear code. Finally, we provide conditions under which each of
these bounds can be achieved by choosing our code to be a subcode of a
Reed-Solomon code, allowing for efficient decoding. This problem has been
considered in multisource multicast network error correction. The problem setup
is also reminiscent of locally repairable codes.Comment: Submitted to ISIT 201
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