Asymptotic performance of distributed detection over random networks

  • Dragana Bajović
  • , Dušan Jakovetić
  • , João Xavier
  • , Bruno Sinopoli
  • , José M.F. Moura

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We show that distributed detection over random networks, or using a random protocol, e.g., of the gossip type, is asymptotically optimal, if the rate of information flow across the random network is large enough. Asymptotic optimality is in the sense of Chernoff information; in other words, we determine when the exponential rate of decay of the error probability for distributed detection is the best possible and equal to the rate of decay of the best centralized detector. The rate of information flow is defined by |log r|, where r is the second largest eigenvalue of the second moment of the random, consensus weight matrix. We quantify interesting tradeoffs in distributed detection, between the rate of information flow and the achievable detection performance.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages3008-3011
Number of pages4
DOIs
StatePublished - 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: May 22 2011May 27 2011

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Country/TerritoryCzech Republic
CityPrague
Period05/22/1105/27/11

Keywords

  • Chernoff information
  • distributed detection
  • information flow
  • random network
  • running consensus

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