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Information flow decomposition for network coding

Research output: Contribution to journal › Article › peer-review

Abstract

We propose a method to identify structural propertics 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.

Original languageEnglish (US)
Pages (from-to)829-848
Number of pages20
JournalIEEE Transactions on Information Theory
Volume52
Issue number3
DOIs
StatePublished - Mar 2006
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Arcs
  • Convolutional codes
  • Decentralized codes
  • Information flow
  • Max-flow min-cut theorem
  • Maximum distance separable (MDS) codes
  • Network coding
  • Network multicast

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