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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

Network Coding in Cognitive Radio Networks: A Comprehensive Survey

TL;DR: A comprehensive survey of NC schemes in cognitive radio networks is provided, highlighting the motivations for and the applications of NC in CRNs.
Journal ArticleDOI

Challenges and Approaches in Large-Scale P2P Media Streaming

TL;DR: By using end hosts' huge bandwidth and computational capacity, peer-to-peer technologies shed new light on media streaming applications' development, yet, locating supplying peers and content delivery path maintenance are two major challenges.
Proceedings ArticleDOI

Network-coded caching-aided multicast for efficient content delivery

TL;DR: This work presents a constructive offline solution that provides the maximum network efficiency that can be achieved by dynamically exploiting network-coded caching and multicasting under arbitrary time-varying demands and provides the transport-storage-popularity tradeoff of a polynomial-time solution that uses uncoded caching according to object popularity and random linear coded transmission.
Proceedings ArticleDOI

Implementation of physical-layer network coding

TL;DR: In this paper, the first implementation of a two-way relay network based on the principle of physical-layer network coding is presented, where XOR mapping is performed on the OFDM samples in each subcarrier rather than on the samples in the time domain.
Journal ArticleDOI

Bounds for Energy-Efficient Survivable IP Over WDM Networks With Network Coding

TL;DR: In this paper, the authors established analytic bounds for the energy efficiency of 1+1 survivable IP over WDM networks using network coding, and the analytic bounds were shown to be in close agreement with our previously reported results.
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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