Information flow decomposition for network coding

被引:112
作者
Fragouli, C [1 ]
Soijanin, E
机构
[1] Ecole Polytech Fed Lausanne, Sch Comp & Commun Sci, CH-1015 Lausanne, Switzerland
[2] Bell Labs, Lucent Technol, Murray Hill, NJ 07974 USA
基金
美国国家科学基金会;
关键词
arcs; convolutional codes; decentralized codes; information flow; max-flow min-cut theorem; maximum distance separable (MDS) codes; network coding; network multicast;
D O I
10.1109/TIT.2005.864435
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a method to identify structural properties of multicast network configurations, by decomposing networks into regions through which the same information flows. This decomposition allows us to show that very different networks are equivalent from a coding point of view, and offers a means to identify such equivalence classes. It also allows us to divide the network coding problem into two almost independent tasks: one of graph theory and the other of classical channel coding theory. This approach to network coding enables us to derive the smallest code alphabet size sufficient to code any network configuration with two sources as a function of the number of receivers in the network. But perhaps the most significant strength of our approach concerns future network coding practice. Namely, we propose deterministic algorithms to specify the coding operations at network nodes without the knowledge of the overall network topology. Such decentralized designs facilitate the construction of codes that can easily accommodate future changes in the network, e.g., addition of receivers and loss of links.
引用
收藏
页码:829 / 848
页数:20
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