2,576 research outputs found
Access vs. Bandwidth in Codes for Storage
Maximum distance separable (MDS) codes are widely used in storage systems to
protect against disk (node) failures. A node is said to have capacity over
some field , if it can store that amount of symbols of the field.
An MDS code uses nodes of capacity to store information
nodes. The MDS property guarantees the resiliency to any node failures.
An \emph{optimal bandwidth} (resp. \emph{optimal access}) MDS code communicates
(resp. accesses) the minimum amount of data during the repair process of a
single failed node. It was shown that this amount equals a fraction of
of data stored in each node. In previous optimal bandwidth
constructions, scaled polynomially with in codes with asymptotic rate
. Moreover, in constructions with a constant number of parities, i.e. rate
approaches 1, is scaled exponentially w.r.t. . In this paper, we focus
on the later case of constant number of parities , and ask the following
question: Given the capacity of a node what is the largest number of
information disks in an optimal bandwidth (resp. access) MDS
code. We give an upper bound for the general case, and two tight bounds in the
special cases of two important families of codes. Moreover, the bounds show
that in some cases optimal-bandwidth code has larger than optimal-access
code, and therefore these two measures are not equivalent.Comment: This paper was presented in part at the IEEE International Symposium
on Information Theory (ISIT 2012). submitted to IEEE transactions on
information theor
MDS Array Codes with Optimal Rebuilding
MDS array codes are widely used in storage systems
to protect data against erasures. We address the rebuilding ratio
problem, namely, in the case of erasures, what is the the fraction
of the remaining information that needs to be accessed in order
to rebuild exactly the lost information? It is clear that when the
number of erasures equals the maximum number of erasures
that an MDS code can correct then the rebuilding ratio is 1
(access all the remaining information). However, the interesting
(and more practical) case is when the number of erasures is
smaller than the erasure correcting capability of the code. For
example, consider an MDS code that can correct two erasures:
What is the smallest amount of information that one needs to
access in order to correct a single erasure? Previous work showed
that the rebuilding ratio is bounded between 1/2 and 3/4 , however,
the exact value was left as an open problem. In this paper, we
solve this open problem and prove that for the case of a single
erasure with a 2-erasure correcting code, the rebuilding ratio is
1/2 . In general, we construct a new family of r-erasure correcting
MDS array codes that has optimal rebuilding ratio of 1/r
in the
case of a single erasure. Our array codes have efficient encoding
and decoding algorithms (for the case r = 2 they use a finite field
of size 3) and an optimal update property
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