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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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Proceedings ArticleDOI

On large-scale peer-to-peer streaming systems with network coding

TL;DR: In this paper, the benefits of network coding for live peer-to-peer (P2P) streaming systems are analyzed. But the authors focus on fundamental properties of P2P streaming systems, with a particular spotlight on network coding.
Journal ArticleDOI

Non-Cooperative Multicast and Facility Location Games

TL;DR: It is proved that finding a Nash equilibrium that minimizes the potential function is NP-hard and an upper bound of O(radicnlog2 n) on the price of anarchy, and a lower bound of Omega(log n/log log n) are established.
Journal ArticleDOI

All-Optical Network Coding

TL;DR: This work presents a heuristic for solving the effectiveness of using network coding for optical-layer dedicated protection of multicast traffic that provides robustness against link failures in the network and shows that it provides near-optimal performance while significantly outperforming existing approaches for dedicated multicast protection.
Proceedings ArticleDOI

Design of network codes for multiple-user multiple-relay wireless networks

TL;DR: For networks with orthogonal channels, it is shown that network codes based on maximum distance separable (MDS) codes can achieve the maximum diversity order of N+1, which is equivalent to achieving the Singleton bound for network error-correction codes.
Journal ArticleDOI

Survey Paper: Opportunistic routing - A review and the challenges ahead

TL;DR: The basic concepts ofortunistic routing are reviewed and components of OR are described with examples, and current trends, issues and challenges of Or are discussed.
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.
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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.
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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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