Error Correction for Cooperative Data Exchange

This paper considers the problem of error correction for a cooperative data exchange (CDE) system, where some clients are compromised or failed and send false messages. Assuming each client possesses a subset of the total messages, we analyze the error correction capability when every client is allo...

Full description

Saved in:
Bibliographic Details
Published in:IEEE communications letters 2012-11, Vol.16 (11), p.1856-1859
Main Authors: Wentu Song, Xiumin Wang, Chau Yuen, Li, T. J., Rongquan Feng
Format: Article
Language:English
Subjects:
Applied sciences
Broadcasting
Clients
Coding
Coding, codes
Cooperative data exchange
Data exchange
Decoding
Error correction
Error correction & detection
Error correction codes
error detection
Exact sciences and technology
Information, signal and communications theory
Linear code
Linear codes
Messages
network coding
Networks
Polynomials
security
Signal and communications theory
Studies
Switching and signalling
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Vectors
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper considers the problem of error correction for a cooperative data exchange (CDE) system, where some clients are compromised or failed and send false messages. Assuming each client possesses a subset of the total messages, we analyze the error correction capability when every client is allowed to broadcast only one linearly-coded message. Our error correction capability bound determines the maximum number of clients that can be compromised or failed without jeopardizing the final decoding solution at each client. We show that deterministic, feasible linear codes exist that can achieve the derived bound. We also evaluate random linear codes, where the coding coefficients are drawn randomly, and then develop the probability for a client to withstand a certain number of compromised or failed peers and successfully deduce the complete message for any network size and any initial message distributions.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2012.100812.121489