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
Journal ArticleDOI

The Complexity of Network Coding With Two Unit-Rate Multicast Sessions

TL;DR: This paper proves that for the 2-URMS networks, the solvability can be determined with time O(|E|); an optimal solution can be obtained in polynomial time and the number of encoding links required to achieve a solution is upper-bounded by max{3,2N - 2}.
Proceedings ArticleDOI

An information-theoretic meta-theorem on edge-cut bounds

TL;DR: It is demonstrated that in these very cases, such edge-cut based bounds are actually `close' to fundamental yielding an approximate characterization of the capacity region for these problems, and suggests a meta-theorem: if there is inherent symmetry either in the network connectivity or in the traffic pattern, then edge- cut bounds are near-fundamental and flows approximately achieve capacity.
Proceedings ArticleDOI

The Capacity Region of a Collection of Multicast Sessions in an Undirected Ring Network

TL;DR: It is demonstrated that routing is rate optimal in this case using new extensions to progressive d-separating edge set bounds.
Proceedings ArticleDOI

Beyond the cut-set bound: Uncertainty computations in network coding with correlated sources

TL;DR: 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, and defines the concept of “uncertainty region” which might be of independent interest.
Journal ArticleDOI

Alignment-Based Network Coding for Two-Unicast-Z Networks

TL;DR: A new linear network coding algorithm for two-unicast-Z networks over the directed acyclic graphs that achieves the rate pair (1, 1) whenever it is feasible in the network is described and a new proof of the classical max-flow min-cut theorem is provided.
References
More filters
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.
Related Papers (5)