TY - GEN
T1 - Quickest Detection of Dynamic Events in Sensor Networks
AU - Zou, Shaofeng
AU - Veeravalli, Venugopal V.
N1 - Funding Information:
This research was supported in part by the NSF under grants CCF 16-18658 and ECCS 14-62311, and by the AFOSR under grant FA9550-16-1-0077, through the University of Illinois at Urbana-Champaign.
PY - 2018/9/10
Y1 - 2018/9/10
N2 - 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.
AB - 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.
KW - Asymptotic optimality
KW - Dynamic event
KW - Quickest change detection
KW - Spartan CuSum
UR - http://www.scopus.com/inward/record.url?scp=85054284740&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2018.8461854
DO - 10.1109/ICASSP.2018.8461854
M3 - Conference contribution
AN - SCOPUS:85054284740
SN - 9781538646588
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 6907
EP - 6911
BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Y2 - 15 April 2018 through 20 April 2018
ER -