Quickest Detection of Significant Events in Structured Networks

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

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


We study the problem of quickest detection of dynamic significant events in structured networks. At some unknown time, an event occurs, and a subset of nodes in the network are affected, which undergo a change in the statistics of their observations. It is assumed that the event propagates dynamically along the edges in the network, in that the affected nodes form a connected subgraph. The event propagation dynamics are assumed to be unknown. The goal is to design a sequential algorithm that can detect a 'significant' event, i.e., when the event has affected no fewer than eta nodes, as quickly as possible, while controlling the false alarm rate. We construct a Network-CuSum (N-CuSum) algorithm that exploits network structure in a computationally efficient way. We show that N-CuSum is adaptive to unknown propagation dynamics, and first-order asymptotically optimal as the false alarm rate goes to zero.

Original languageEnglish (US)
Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781538692189
StatePublished - Jul 2 2018
Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
Duration: Oct 28 2018Oct 31 2018

Publication series

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


Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Country/TerritoryUnited States
CityPacific Grove

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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