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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.

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Citations
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Journal ArticleDOI

Theory of Secure Network Coding

TL;DR: This tutorial paper presents a model for secure network coding and then a necessary and sufficient condition for a linear network code to be secure, and optimal methods to construct linear secure network codes are provided.
Journal ArticleDOI

Dualities Between Entropy Functions and Network Codes

TL;DR: In this paper, the capacity region of multisource network coding is given in terms of the set of entropy functions Gamma*, which is a duality between entropy functions and network codes.
Proceedings ArticleDOI

Loss-aware network coding for unicast wireless sessions: design, implementation, and performance evaluation

TL;DR: This paper shows that the design space for effective redundancy in local network coding is quite large, which makes optimal formulations of the problem hard to realize in practice and proposes a suite of algorithms, called CLONE, that can lead to further throughput gains in multi-hop wireless scenarios.
Proceedings ArticleDOI

P-Coding: Secure Network Coding against Eavesdropping Attacks

TL;DR: P-Coding is proposed, a novel security scheme against eavesdropping attacks in network coding that can efficiently thwart global eavesdroppers in a transparent way and is also featured in scalability and robustness, which enable it to be integrated into practical network coded systems.
Journal ArticleDOI

Differential Modulation for Bidirectional Relaying With Analog Network Coding

TL;DR: In this article, an analog network coding scheme with differential modulation (ANC-DM) using amplify-and-forward protocol for bidirectional relay networks when neither the source nodes nor the relay knows the channel state information (CSI) is analyzed and a simple asymptotic bit error rate (BER) expression is derived.
References
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Book

Elements of information theory

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

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

TL;DR: These rates are shown to be optimal for deterministic distortion measures for random variables and Shannon mutual information.
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