scispace - formally typeset
Open AccessJournal ArticleDOI

Edge-Cut Bounds on Network Coding Rates

Reads0
Chats0
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
Posted Content

Capacity of Multiple Unicast in Wireless Networks: A Polymatroidal Approach

TL;DR: The key engineering insight is that layered architectures, common in the engineering-design of wireless networks, can have near-optimal performance if the locality over which physical-layer schemes should operate is carefully designed.
Journal ArticleDOI

A Geometric Perspective to Multiple-Unicast Network Coding

TL;DR: A geometric framework is presented for analyzing the multiple-unicast network coding conjecture, which states that for multiple unicast sessions in an undirected network, network coding is equivalent to routing.
Proceedings ArticleDOI

Multicast Throughput Order of Network Coding in Wireless Ad-hoc Networks

TL;DR: This work implies that the network coding gain is bounded by a constant for all values of m, and has an exception when m is bound by O(n/(log(n))3) and Ω(n/log( n).
Proceedings ArticleDOI

Graph Spectra of Carbon Nanotube Networks

TL;DR: This paper examines potential benefits from the perspective of using individual nanotubes within random carbon nanotube networks (CNT) to carry information, clearly distinct from traditional, potentially less efficient, approaches of using CNT networks to construct transistors.
Posted Content

On the Solvability of 2-pair Unicast Networks — A Cut-based Characterization

TL;DR: It is shown that the solvability of a 2-pair unicast problem is completely determined and a subnetwork decomposition/combination approach is proposed to investigate the single rate 2- Pair unicorn problem.
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)