Journal ArticleDOI
Linear network coding
TLDR
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.Abstract:
Consider a communication network in which certain source nodes multicast information to other nodes on the network in the multihop fashion where every node can pass on any of its received data to others. We are interested in how fast each node can receive the complete information, or equivalently, what the information rate arriving at each node is. Allowing a node to encode its received data before passing it on, the question involves optimization of the multicast mechanisms at the nodes. Among the simplest coding schemes is linear coding, which regards a block of data as a vector over a certain base field and allows a node to apply a linear transformation to a vector before passing it on. We formulate this multicast problem and prove that linear coding suffices to achieve the optimum, which is the max-flow from the source to each receiving node.read more
Citations
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Journal ArticleDOI
Network information flow
TL;DR: 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.
Journal ArticleDOI
A Random Linear Network Coding Approach to Multicast
TL;DR: This work presents a distributed random linear network coding approach for transmission and compression of information in general multisource multicast networks, and shows that this approach can take advantage of redundant network capacity for improved success probability and robustness.
Journal ArticleDOI
An algebraic approach to network coding
Ralf Koetter,Muriel Medard +1 more
TL;DR: For the multicast setup it is proved that there exist coding strategies that provide maximally robust networks and that do not require adaptation of the network interior to the failure pattern in question.
Book
Network Information Theory
Abbas El Gamal,Young-Han Kim +1 more
TL;DR: In this article, a comprehensive treatment of network information theory and its applications is provided, which provides the first unified coverage of both classical and recent results, including successive cancellation and superposition coding, MIMO wireless communication, network coding and cooperative relaying.
Journal ArticleDOI
XORs in the air: practical wireless network coding
TL;DR: The results show that using COPE at the forwarding layer, without modifying routing and higher layers, increases network throughput, and the gains vary from a few percent to several folds depending on the traffic pattern, congestion level, and transport protocol.
References
More filters
Journal ArticleDOI
Network information flow
TL;DR: 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.
Proceedings ArticleDOI
Network coding for large scale content distribution
TL;DR: It is demonstrated through simulations of scenarios of practical interest that the expected file download time improves by more than 20-30% with network coding compared to coding at the server only and, byMore than 2-3 times compared to sending unencoded information.
Journal ArticleDOI
Polynomial time algorithms for multicast network code construction
Sidharth Jaggi,Peter Sanders,Philip A. Chou,Michelle Effros,Sebastian Egner,K. Jain,Ludo Tolhuizen +6 more
TL;DR: Deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity are given and extended to integer capacities and to codes that are tolerant to edge failures.
Book
A First Course in Information Theory
TL;DR: This book provides the first comprehensive treatment of the theory of I-Measure, network coding theory, Shannon and non-Shannon type information inequalities, and a relation between entropy and group theory.
Proceedings ArticleDOI
Polynomial time algorithms for network information flow
TL;DR: The main result are polynomial time algorithms for constructing coding schemes for multicasting at the maximal data rate and graphs where without coding the rate must be a factor Ω(log|V|) smaller.