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https://doi.org/10.1109/infcom...
Article . 2012 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2011
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2011
Data sources: DBLP
DBLP
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Data sources: DBLP
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Simple regenerating codes: Network coding for cloud storage

Authors: Dimitris S. Papailiopoulos; Jianqiang Luo; Alexandros G. Dimakis; Cheng Huang 0002; Jin Li 0001;

Simple regenerating codes: Network coding for cloud storage

Abstract

Network codes designed specifically for distributed storage systems have the potential to provide dramatically higher storage efficiency for the same availability. One main challenge in the design of such codes is the exact repair problem: if a node storing encoded information fails, in order to maintain the same level of reliability we need to create encoded information at a new node. One of the main open problems in this emerging area has been the design of simple coding schemes that allow exact and low cost repair of failed nodes and have high data rates. In particular, all prior known explicit constructions have data rates bounded by 1/2. In this paper we introduce the first family of distributed storage codes that have simple look-up repair and can achieve arbitrarily high rates. Our constructions are very simple to implement and perform exact repair by simple XORing of packets. We experimentally evaluate the proposed codes in a realistic cloud storage simulator and show significant benefits in both performance and reliability compared to replication and standard Reed-Solomon codes.

9 pages, 10 figures, submitted for publication

Keywords

Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Information Theory, Information Theory (cs.IT), Distributed, Parallel, and Cluster Computing (cs.DC)

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    133
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
133
Top 10%
Top 1%
Top 1%
Green