Quickest Detection of Dynamic Events in Sensor Networks

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

Abstract

We consider the problem of quickest detection of dynamic events in sensor networks. After an event occurs, a number of sensors are affected and undergo a change in the statistics of their observations. We assume that the event is dynamic and can propagate with time, i.e., different sensors perceive the event at different times. The goal is to design a sequential algorithm that can detect when the event has affected no less than η sensors as quickly as possible, subject to false alarm constraints. We design a computationally efficient algorithm that is adaptive to unknown propagation dynamics, and demonstrate its asymptotic optimality as the false alarm rate goes to zero. We also provide numerical simulations to validate our theoretical results.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6907-6911
Number of pages5
ISBN (Print)9781538646588
DOIs
StatePublished - Sep 10 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: Apr 15 2018Apr 20 2018

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Other

Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period4/15/184/20/18

Keywords

  • Asymptotic optimality
  • Dynamic event
  • Quickest change detection
  • Spartan CuSum

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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