81,221 research outputs found
Decentralized Erasure Codes for Distributed Networked Storage
We consider the problem of constructing an erasure code for storage over a
network when the data sources are distributed. Specifically, we assume that
there are n storage nodes with limited memory and k<n sources generating the
data. We want a data collector, who can appear anywhere in the network, to
query any k storage nodes and be able to retrieve the data. We introduce
Decentralized Erasure Codes, which are linear codes with a specific randomized
structure inspired by network coding on random bipartite graphs. We show that
decentralized erasure codes are optimally sparse, and lead to reduced
communication, storage and computation cost over random linear coding.Comment: to appear in IEEE Transactions on Information Theory, Special Issue:
Networking and Information Theor
On Counteracting Byzantine Attacks in Network Coded Peer-to-Peer Networks
Random linear network coding can be used in peer-to-peer networks to increase
the efficiency of content distribution and distributed storage. However, these
systems are particularly susceptible to Byzantine attacks. We quantify the
impact of Byzantine attacks on the coded system by evaluating the probability
that a receiver node fails to correctly recover a file. We show that even for a
small probability of attack, the system fails with overwhelming probability. We
then propose a novel signature scheme that allows packet-level Byzantine
detection. This scheme allows one-hop containment of the contamination, and
saves bandwidth by allowing nodes to detect and drop the contaminated packets.
We compare the net cost of our signature scheme with various other Byzantine
schemes, and show that when the probability of Byzantine attacks is high, our
scheme is the most bandwidth efficient.Comment: 26 pages, 9 figures, Submitted to IEEE Journal on Selected Areas in
Communications (JSAC) "Mission Critical Networking
Coding for Fast Content Download
We study the fundamental trade-off between storage and content download time.
We show that the download time can be significantly reduced by dividing the
content into chunks, encoding it to add redundancy and then distributing it
across multiple disks. We determine the download time for two content access
models - the fountain and fork-join models that involve simultaneous content
access, and individual access from enqueued user requests respectively. For the
fountain model we explicitly characterize the download time, while in the
fork-join model we derive the upper and lower bounds. Our results show that
coding reduces download time, through the diversity of distributing the data
across more disks, even for the total storage used.Comment: 8 pages, 6 figures, conferenc
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