2 research outputs found
Tradeoff for Heterogeneous Distributed Storage Systems between Storage and Repair Cost
In this paper, we consider heterogeneous distributed storage systems (DSSs)
having flexible reconstruction degree, where each node in the system has
dynamic repair bandwidth and dynamic storage capacity. In particular, a data
collector can reconstruct the file at time using some arbitrary nodes in
the system and for a node failure the system can be repaired by some set of
arbitrary nodes. Using - bound, we investigate the fundamental
tradeoff between storage and repair cost for our model of heterogeneous DSS. In
particular, the problem is formulated as bi-objective optimization linear
programing problem. For an arbitrary DSS, it is shown that the calculated
- bound is tight.Comment: 10 pages, 5 figures, draf
Bandwidth Cost of Code Conversions in Distributed Storage: Fundamental Limits and Optimal Constructions
Erasure codes have become an integral part of distributed storage systems as
a tool for providing data reliability and durability under the constant threat
of device failures. In such systems, an code over a finite field
encodes message symbols into codeword symbols from
which are then stored on different nodes in the system.
Recent work has shown that significant savings in storage space can be obtained
by tuning and to variations in device failure rates. Such a tuning
necessitates code conversion: the process of converting already encoded data
under an initial code to its equivalent under a final
code. The default approach to conversion is to reencode data, which places
significant burden on system resources. Convertible codes are a recently
proposed class of codes for enabling resource-efficient conversions. Existing
work on convertible codes has focused on minimizing access cost, i.e., the
number of code symbols accessed during conversion. Bandwidth, which corresponds
to the amount of data read and transferred, is another important resource to
optimize.
In this paper, we initiate the study on the fundamental limits on bandwidth
used during code conversion and present constructions for bandwidth-optimal
convertible codes. First, we model the code conversion problem using network
information flow graphs with variable capacity edges. Second, focusing on MDS
codes and an important parameter regime called the merge regime, we derive
tight lower bounds on the bandwidth cost of conversion. The derived bounds show
that bandwidth cost can be significantly reduced even in regimes where access
cost cannot be reduced as compared to the default approach. Third, we present a
new construction for MDS convertible codes which matches the proposed lower
bound and is thus bandwidth-optimal during conversion