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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Proceedings ArticleDOI
Network Error Correction Coding in Packetized Networks
TL;DR: The existence of codes that can correct errors up to the full error correction capability in singleton bound is proved and it is shown that the error can be corrected with very high probability under reasonable assumptions.
Proceedings ArticleDOI
Fundamental limits of caching
TL;DR: This paper proposes a novel caching approach that can achieve a significantly larger reduction in peak rate compared to previously known caching schemes, and argues that the performance of the proposed scheme is within a constant factor from the information-theoretic optimum for all values of the problem parameters.
Proceedings ArticleDOI
The encoding complexity of network coding
TL;DR: It is proved that in an acyclic coding network, the number of encoding nodes required to achieve the capacity of the network is bounded h3k2, where B is the minimum size of the feedback link set.
Journal ArticleDOI
Network coding-based protection of many-to-one wireless flows
TL;DR: This paper derives and proves the necessary and sufficient conditions for the solution on a restricted network topology, and shows how to generalize the sufficient and necessary conditions to work with any other topology.
Proceedings ArticleDOI
Nuclei: GPU-Accelerated Many-Core Network Coding
TL;DR: This work shows how the GPU, with a design involving thousands of lightweight threads, can boost network coding performance significantly, and can be deployed as an attractive alternative and complementary solution to multi-core servers, by offering a better price/performance advantage.
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.