Distributed Quickest Detection of Significant Events in Networks

Shaofeng Zou, Venugopal V. Veeravalli, Jian Li, Don Towsley, Ananthram Swami

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

Abstract

The problem of quickest detection of significant events in networks is studied. A distributed setting is investigated, where there is no fusion center, and each node only communicates with its neighbors. After an event occurs in the network, a number of nodes are affected, which changes the statistics of their observations. The nodes may possibly perceive the event at different times. The goal is to design a distributed sequential detection rule that can detect when the event is »significant», i.e., the event has affected no less than η nodes, as quickly as possible, subject to false alarm constraints. A distributed algorithm is proposed, which is based on a novel combination of the alternating direction method of multipliers (ADMM) and average consensus approaches. Numerical results are provided to demonstrate the performance of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8454-8458
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: May 12 2019May 17 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period5/12/195/17/19

Keywords

  • ADMM
  • average consensus
  • distributed algorithm
  • network event detection
  • quickest change detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Distributed Quickest Detection of Significant Events in Networks'. Together they form a unique fingerprint.

Cite this