Quickest Detection of a Dynamic Anomaly in a Heterogeneous Sensor Network

Georgios Rovatsos, Venugopal V. Veeravalli, George V. Moustakides

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

Abstract

The problem studied is one of quickest detection of an anomaly that emerges in a sensor network, and which may move across the network after it emerges. Each sensor in the network is characterized by a non-anomalous and an anomalous data-generating distribution, and these distributions could be different across the sensors. Initially, the observations at all the sensors are generated according to their corresponding non-anomalous distribution. After some unknown but deterministic time instant, a dynamic anomaly emerges in the network, affecting a different sensor as time progresses. The observations generated by the affected sensor follow the corresponding anomalous distribution. The goal is to detect the onset of the dynamic anomaly as quickly as possible, subject to constraints on the frequency of false alarms. This detection problem is posed in a quickest change detection framework where candidate stopping procedures are evaluated according to a delay metric that considers the worst trajectory of the dynamic anomaly. A detection rule is proposed and established to be asymptotically optimal as the mean time to false alarm goes to infinity. Finally, numerical results are provided to validate our theoretical analysis.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1171-1176
Number of pages6
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: Jul 21 2020Jul 26 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
CountryUnited States
CityLos Angeles
Period7/21/207/26/20

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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