Journal ArticleDOI
Network information flow
TLDR
This work reveals that it is in general not optimal to regard the information to be multicast as a "fluid" which can simply be routed or replicated, and by employing coding at the nodes, which the work refers to as network coding, bandwidth can in general be saved.Abstract:
We introduce a new class of problems called network information flow which is inspired by computer network applications. Consider a point-to-point communication network on which a number of information sources are to be multicast to certain sets of destinations. We assume that the information sources are mutually independent. The problem is to characterize the admissible coding rate region. This model subsumes all previously studied models along the same line. We study the problem with one information source, and we have obtained a simple characterization of the admissible coding rate region. Our result can be regarded as the max-flow min-cut theorem for network information flow. Contrary to one's intuition, our work reveals that it is in general not optimal to regard the information to be multicast as a "fluid" which can simply be routed or replicated. Rather, by employing coding at the nodes, which we refer to as network coding, bandwidth can in general be saved. This finding may have significant impact on future design of switching systems.read more
Citations
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Book
Cooperative Communications
TL;DR: This article reviews progress in cooperative communication networks and intends its presentation to be a tutorial for the reader who is familiar with information theory concepts but has not actively followed the field.
Journal ArticleDOI
Growth codes: maximizing sensor network data persistence
TL;DR: This paper design and analyze techniques to increase "persistence" of sensed data, so that data is more likely to reach a data sink, even as network nodes fail, by replicating data compactly at neighboring nodes using novel "Growth Codes" that increase in efficiency as data accumulates at the sink.
Journal ArticleDOI
On the Index Coding Problem and Its Relation to Network Coding and Matroid Theory
TL;DR: It is shown that vectorlinear codes outperform scalar linear index codes and that vector linear codes are insufficient for achieving the optimum number of transmissions.
Proceedings ArticleDOI
Polynomial time algorithms for network information flow
TL;DR: The main result are polynomial time algorithms for constructing coding schemes for multicasting at the maximal data rate and graphs where without coding the rate must be a factor Ω(log|V|) smaller.
Journal ArticleDOI
Network Error Correction, I: Basic Concepts and Upper Bounds
Raymond W. Yeung,Ning Cai +1 more
TL;DR: inspired by network coding, a new paradigm called network error correction is introduced and the basic concepts and the network generalizations of the Hamming bound and the Singleton bound are discussed.
References
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Book
Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI
Factor graphs and the sum-product algorithm
TL;DR: A generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph, that computes-either exactly or approximately-various marginal functions derived from the global function.
Journal ArticleDOI
Noiseless coding of correlated information sources
David Slepian,Jack K. Wolf +1 more
TL;DR: The minimum number of bits per character R_X and R_Y needed to encode these sequences so that they can be faithfully reproduced under a variety of assumptions regarding the encoders and decoders is determined.
Journal ArticleDOI
Linear network coding
TL;DR: This work forms this multicast problem and proves that linear coding suffices to achieve the optimum, which is the max-flow from the source to each receiving node.
Journal ArticleDOI
Achievable rates for multiple descriptions
Abbas El Gamal,Thomas M. Cover +1 more
TL;DR: These rates are shown to be optimal for deterministic distortion measures for random variables and Shannon mutual information.