scispace - formally typeset
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.

read more

Content maybe subject to copyright    Report

Citations
More filters
Book

Network Information Theory

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.
Book

Cooperative Communications

TL;DR: This article reviews progress in cooperative communication networks and intends its presentation to be a tutorial for the reader who is familiar with information theory concepts but has not actively followed the field.
Book

Topics in Multi-User Information Theory

TL;DR: This survey builds up knowledge on random coding, binning, superposition coding, and capacity converses by introducing progressively more sophisticated tools for a selection of source and channel models.
Journal ArticleDOI

Networks, Matroids, and Non-Shannon Information Inequalities

TL;DR: The Vamos network is constructed, and it is proved that Shannon-type information inequalities are insufficient even for computing network coding capacities of multiple-unicast networks.
Book

Principles Of Cognitive Radio

TL;DR: 1. The concept of cognitive radio, capacity of cognitiveRadio networks, and Propagation issues for cognitive radio: a review.
References
More filters

The Switch Ware Active Network Architecture

TL;DR: The SwitchWare active network architecture is a novel approach to achieving this balance using three layers: active packets, which contain mobile programs that replace traditional packets; active extensions, which provide services on the network elements and can be dynamically loaded; and a secure active router infrastructure, which forms a high-integrity base on which the security of the other layers depends.
Journal ArticleDOI

The SwitchWare active network architecture

TL;DR: SwitchWare as mentioned in this paper is an active network architecture that uses three layers: active packets, which contain mobile programs that replace traditional packets; active extensions, which provide services on the network elements and can be dynamically loaded; and a secure active router infrastructure, which forms a high-integrity base on which the security of the other layers depends.
Proceedings ArticleDOI

PLAN: a packet language for active networks

TL;DR: This paper has successfully applied the PLAN programming environment to implement an IP-free internetwork and provides a guarantee that PLAN programs use a bounded amount of network resources.
Journal ArticleDOI

Multicommodity flows in planar graphs

TL;DR: This paper solves the problem of when is there a flow for each i, between s i and t i and of value q i, such that the total flow through each edge does not exceed its capacity.
Journal ArticleDOI

Capacity results for the discrete memoryless network

TL;DR: Several techniques for improving the bounds are developed: (1) causally conditioned entropy and directed information simplify the inner bounds, (2) code trellises serve as simple code trees, (3) superposition coding and binning with code trees improves rates.
Related Papers (5)