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Edge-Cut Bounds on Network Coding Rates

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TLDR
A new bound on communication rates is developed that applies to network coding, which is a promising active network application that has processors transmit packets that are general functions, for example a bit-wise XOR of selected received packets.
Abstract
Active networks are network architectures with processors that are capable of executing code carried by the packets passing through them. A critical network management concern is the optimization of such networks and tight bounds on their performance serve as useful design benchmarks. A new bound on communication rates is developed that applies to network coding, which is a promising active network application that has processors transmit packets that are general functions, for example a bit-wise XOR, of selected received packets. The bound generalizes an edge-cut bound on routing rates by progressively removing edges from the network graph and checking whether certain strengthened d-separation conditions are satisfied. The bound improves on the cut-set bound and its efficacy is demonstrated by showing that routing is rate-optimal for some commonly cited examples in the networking literature.

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Proceedings ArticleDOI

Extensions and limits to vertex sparsification

TL;DR: This work proves that there exist flow sparsifiers that simultaneously preserve the congestion of all multicommodity flows within an O(log k / log log k)-factor where |K| = k and improves to O(1) if G excludes any fixed minor.
Journal ArticleDOI

Network Coding and Matroid Theory

TL;DR: This tutorial paper reviews many connections between matroids and network coding theory, with specific emphasis on network solvability, admissible network alphabet sizes, linear coding, and network capacity.
Posted Content

A Theory of Network Equivalence

TL;DR: An equivalence result for network capacity is described that a collection of demands can be met on the given network if and only if it can be meet on another network where each noisy link is replaced by a noiseless bit pipe with throughput equal to the noisy link capacity.
Proceedings ArticleDOI

On a theory of network equivalence

TL;DR: In this paper, the equivalence result for network capacity was shown for a network of noisy, independent, memoryless links, where a collection of demands can be met on the given network if and only if it can be matched on another network where each noisy link is replaced by a noiseless bit pipe with throughput equal to the noisy link capacity.
Journal ArticleDOI

Network Coding Capacity Regions via Entropy Functions

TL;DR: It is proved that for the incremental multicast problem and for the single-source secure network coding problem, characterization of the achievable set can be very hard and linear network codes may not be optimal.
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.
Book

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
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.
Book

Flows in networks

TL;DR: Ford and Fulkerson as mentioned in this paper set the foundation for the study of network flow problems and developed powerful computational tools for solving and analyzing network flow models, and also furthered the understanding of linear programming.
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