Distributed localization and clustering using data correlation and the Occam's razor principle

Pankaj K. Agarwal, Alon Efrat, Chris Gniady, Joseph S.B. Mitchell, Valentin Polishchuk, Girishkumar R. Sabhnani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We present a distributed algorithm for computing a combined solution to three problems in sensor networks: localization, clustering, and sensor suspension. Assuming that initially only a rough approximation of the sensor positions is known, we show how one can use sensor measurements to refine the set of possible sensor locations, to group the sensors into clusters with linearly correlated measurements, and to decide which sensors may suspend transmission without jeopardizing the consistency of the collected data. Our algorithm applies the "Occam's razor principle" by computing a "simplest" explanation for the data gathered from the network. We also present centralized algorithms, as well as efficient heuristics.

Original languageEnglish (US)
Title of host publication2011 International Conference on Distributed Computing in Sensor Systems and Workshops, DCOSS'11
DOIs
StatePublished - Sep 12 2011
Event7th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS'11 - Barcelona, Spain
Duration: Jun 27 2011Jun 29 2011

Publication series

Name2011 International Conference on Distributed Computing in Sensor Systems and Workshops, DCOSS'11

Other

Other7th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS'11
CountrySpain
CityBarcelona
Period6/27/116/29/11

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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