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Open AccessJournal ArticleDOI

Edge-Cut Bounds on Network Coding Rates

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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Citations
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Journal ArticleDOI

Capacity of Multiple Unicast in Wireless Networks: A Polymatroidal Approach

TL;DR: In this article, the authors show that for a given channel and its reciprocal channel, the min cut upper bound is within a logarithmic factor of the number of sources of the max flow.
Journal ArticleDOI

Beyond the Cut-Set Bound: Uncertainty Computations in Network Coding With Correlated Sources

TL;DR: In this paper, the authors introduce a new technique for proving converses for the problem of transmission of correlated sources in networks, which results in bounds that are tighter than the corresponding cut-set bounds.
Proceedings ArticleDOI

A Multimessage Capacity Region for Undirected Ring Networks

TL;DR: An extension of the Japanese theorem to multiple multicast sessions is developed and it is demonstrated that routing is rate-optimal using new extensions to progressive d-separating edge set bounds.
Proceedings ArticleDOI

Coding in Undirected Graphs Is Either Very Helpful or Not Helpful at All

TL;DR: It is proved that any undirected network with $k$ source-sink pairs that exhibits a $(1+\varepsilon)$ gap between its MCF rate and its network coding rate can be used to construct a family of graphs whose gap is $\log(|G'|)^c$ for some constant $c < 1$.
Book ChapterDOI

Principles of Cognitive Radio: Capacity of cognitive radio networks

TL;DR: In this article, the fundamental capacity limits and associated transmission techniques for different cognitive radio network paradigms are developed based on the premise that the cognitive radios of secondary users are intelligent wireless communication devices that exploit side information about their environment to improve spectrum utilization.
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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