A Consensus-based Approach for Distributed Quickest Detection of Significant Events in Networks

Jian Li, Don Towsley, Shaofeng Zou, Venugopal V. Veeravalli, Gabriela Ciocarlie

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

Abstract

This paper studies the problem of quickest detection of significant events in networks, where nodes undergo a change in the data generating the distributions of their observations due to events that occurred at some unknown time. Events can propagate dynamically along edges in the network to affect more nodes over time; however, the propagation dynamics are assumed to be unknown. A consensus-based distributed-detection algorithm is proposed to detect a 'significant' event, i.e., at least η nodes have been affected by the event, as quickly as possible, subject to false alarm constraints. It is shown that the proposed distributed algorithm achieves an equivalent performance to that of a centralized algorithm, which was shown to be first-order asymptotically optimal, as the false alarm rate goes to zero. Finally, numerical experiments are provided to evaluate the efficiency of the proposed algorithm.

Original languageEnglish (US)
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1881-1884
Number of pages4
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: Nov 3 2019Nov 6 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Country/TerritoryUnited States
CityPacific Grove
Period11/3/1911/6/19

Keywords

  • Anomaly detection
  • consensus algorithm
  • distributed algorithm
  • quickest change detection
  • sequential change detection

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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