An information theoretic approach to network tomography

Wendy K. Tam Cho, George Judge

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, we formulate an information theoretic approach to information recovery for a network flow transportation problem as an ill-posed inverse problem and use nonparametric information theoretic methods to recover the unknown adaptive-intelligent behaviour traffic flows. We indicate how, in general, information theoretic methods may provide a solution to the ill-posed inverse information flow problems, when a function must be inferred from insufficient sample information. As an application, we examine a data set which comprised traffic volumes at Bell Labs.

Original languageEnglish (US)
Pages (from-to)1-6
Number of pages6
JournalApplied Economics Letters
Volume22
Issue number1
DOIs
StatePublished - Jan 2 2015

Keywords

  • Cressie–Read divergence
  • information theoretic methods
  • inverse problem
  • link measurements
  • network tomography

ASJC Scopus subject areas

  • Economics and Econometrics

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