TY - GEN
T1 - Quickest Change Detection in Anonymous Heterogeneous Sensor Networks
AU - Sun, Zhongchang
AU - Zou, Shaofeng
AU - Li, Qunwei
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center. The sensors are clustered into K groups, and different groups follow different data generating distributions. At some unknown time, an event occurs in the network and changes the data generating distribution of the sensors. The goal is to detect the change as quickly as possible, subject to false alarm constraints. The anonymous setting is studied in this paper, where at each time step, the fusion center receives n unordered samples. The fusion center does not know which sensor each sample comes from, and thus does not know its exact distribution. In this paper, a simple optimality proof is derived for the Mixture Likelihood Ratio Test (MLRT), which was constructed and proved to be optimal for the non-sequential anonymous setting in [1]. For the QCD problem, a mixture CuSum algorithm is constructed in this paper, and is further shown to be optimal under Lorden's criterion [2].
AB - The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center. The sensors are clustered into K groups, and different groups follow different data generating distributions. At some unknown time, an event occurs in the network and changes the data generating distribution of the sensors. The goal is to detect the change as quickly as possible, subject to false alarm constraints. The anonymous setting is studied in this paper, where at each time step, the fusion center receives n unordered samples. The fusion center does not know which sensor each sample comes from, and thus does not know its exact distribution. In this paper, a simple optimality proof is derived for the Mixture Likelihood Ratio Test (MLRT), which was constructed and proved to be optimal for the non-sequential anonymous setting in [1]. For the QCD problem, a mixture CuSum algorithm is constructed in this paper, and is further shown to be optimal under Lorden's criterion [2].
KW - Anonymous
KW - heterogeneous
KW - hypothesis testing
KW - mixture CuSum
KW - sequential change detection
UR - https://www.scopus.com/pages/publications/85089210739
U2 - 10.1109/ICASSP40776.2020.9054079
DO - 10.1109/ICASSP40776.2020.9054079
M3 - Conference contribution
AN - SCOPUS:85089210739
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 5925
EP - 5929
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -