1,686 research outputs found
On Secure Distributed Data Storage Under Repair Dynamics
We address the problem of securing distributed storage systems against
passive eavesdroppers that can observe a limited number of storage nodes. An
important aspect of these systems is node failures over time, which demand a
repair mechanism aimed at maintaining a targeted high level of system
reliability. If an eavesdropper observes a node that is added to the system to
replace a failed node, it will have access to all the data downloaded during
repair, which can potentially compromise the entire information in the system.
We are interested in determining the secrecy capacity of distributed storage
systems under repair dynamics, i.e., the maximum amount of data that can be
securely stored and made available to a legitimate user without revealing any
information to any eavesdropper. We derive a general upper bound on the secrecy
capacity and show that this bound is tight for the bandwidth-limited regime
which is of importance in scenarios such as peer-to-peer distributed storage
systems. We also provide a simple explicit code construction that achieves the
capacity for this regime.Comment: 5 pages, 4 figures, to appear in Proceedings of IEEE ISIT 201
Distributed Data Storage with Minimum Storage Regenerating Codes - Exact and Functional Repair are Asymptotically Equally Efficient
We consider a set up where a file of size M is stored in n distributed
storage nodes, using an (n,k) minimum storage regenerating (MSR) code, i.e., a
maximum distance separable (MDS) code that also allows efficient exact-repair
of any failed node. The problem of interest in this paper is to minimize the
repair bandwidth B for exact regeneration of a single failed node, i.e., the
minimum data to be downloaded by a new node to replace the failed node by its
exact replica. Previous work has shown that a bandwidth of B=[M(n-1)]/[k(n-k)]
is necessary and sufficient for functional (not exact) regeneration. It has
also been shown that if k < = max(n/2, 3), then there is no extra cost of exact
regeneration over functional regeneration. The practically relevant setting of
low-redundancy, i.e., k/n>1/2 remains open for k>3 and it has been shown that
there is an extra bandwidth cost for exact repair over functional repair in
this case. In this work, we adopt into the distributed storage context an
asymptotically optimal interference alignment scheme previously proposed by
Cadambe and Jafar for large wireless interference networks. With this scheme we
solve the problem of repair bandwidth minimization for (n,k) exact-MSR codes
for all (n,k) values including the previously open case of k > \max(n/2,3). Our
main result is that, for any (n,k), and sufficiently large file sizes, there is
no extra cost of exact regeneration over functional regeneration in terms of
the repair bandwidth per bit of regenerated data. More precisely, we show that
in the limit as M approaches infinity, the ratio B/M = (n-1)/(k(n-k))$
Encoding and Decoding Techniques for Distributed Data Storage Systems
Dimensionality reduction is the conversion of high-dimensional data into a meaningful representation of reduced data. Preferably, the reduced representation has a dimensionality that corresponds to the essential dimensionality of the data. The essential dimensionality of data is the minimum number of parameters needed to account for the observed properties of the data [4]. Dimensionality reduction is important in many domains, since it facilitates classification, visualization, and compression of high-dimensional data, by helpful the curse of dimensionality and other undesired properties of high-dimensional spaces [5]. Dimension reduction can be beneficial not only for reasons of computational efficiency but also because it can improve the accuracy of the analysis. In this research area, it significantly reduces the storage spaces
Policy-based SLA storage management model for distributed data storage services
There is high demand for storage related services supporting scientists in their research activities. Those services are expected to provide not only capacity but also features allowing for more flexible and cost efficient usage. Such features include easy multiplatform data access, long term data retention, support for performance and cost differentiating of SLA restricted data access. The paper presents a policy-based SLA storage management model for distributed data storage services. The model allows for automated management of distributed data aimed at QoS provisioning with no strict resource reservation. The problem of providing users with the required QoS requirements is complex, and therefore the model implements heuristic approach for solving it. The corresponding system architecture, metrics and methods for SLA focused storage management are developed and tested in a real, nationwide environment
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