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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

Adversarial models and resilient schemes for network coding

TL;DR: In this paper, Jaggi et al. presented a distributed polynomial-time rate-optimal network-coding scheme that works in the presence of Byzantine faults and augmented them with three, arguably realistic, models.
Proceedings ArticleDOI

Joint Network Coding and Superposition Coding for Multi-User Information Exchange in Wireless Relaying Networks

TL;DR: It is shown that the maximum coding gains of the JNSC and PNC schemes compared with the PTD scheme is achieved as the transmission rate of each node is one third of the sum rate in the network.
Proceedings ArticleDOI

M-user cooperative wireless communications based on nonbinary network codes

TL;DR: This work investigates the existence of deterministic dynamic-network codes for multiple-user networks, and shows that the diversity order of the proposed scheme can achieve 2M − 1, the min-cut for cooperative networks with a dynamic topology.
Journal ArticleDOI

Adaptive data aggregation and energy efficiency using network coding in a clustered wireless sensor network: An analytical approach

TL;DR: The proposed ADANC strategy provides reduction of traffic inside a cluster and thus improves the energy efficiency of the bottleneck zone and it has been shown that the packet delivery ratio improves with the proposed scheme in a cluster.
Journal ArticleDOI

Buffer-aware network coding for wireless networks

TL;DR: A novel cross-layer approach, which is referred to as Buffer-Aware Network Coding, or BANC, which allows transmission of some packets without network coding to reduce the packet delay and results will show that the proposed approach can strike the optimal tradeoff between power efficiency and QoS.
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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