TY - GEN
T1 - A Computationally Efficient Algorithm for Quickest Change Detection in Anonymous Heterogeneous Sensor Networks
AU - Sun, Zhongchang
AU - Li, Qunwei
AU - Zhang, Ruizhi
AU - Zou, Shaofeng
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/7/12
Y1 - 2021/7/12
N2 - The problem of quickest change detection in anonymous heterogeneous sensor networks is studied. 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, where at each time step, the fusion center receives unordered samples without knowing which sensor each sample comes from, and thus does not know its exact distribution. In [1], an optimal algorithm was provided, which however is not computational efficient for large networks. In this paper, a computationally efficient test is proposed and a novel theoretical characterization of its false alarm rate is further developed.
AB - The problem of quickest change detection in anonymous heterogeneous sensor networks is studied. 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, where at each time step, the fusion center receives unordered samples without knowing which sensor each sample comes from, and thus does not know its exact distribution. In [1], an optimal algorithm was provided, which however is not computational efficient for large networks. In this paper, a computationally efficient test is proposed and a novel theoretical characterization of its false alarm rate is further developed.
UR - https://www.scopus.com/pages/publications/85115044970
U2 - 10.1109/ISIT45174.2021.9517884
DO - 10.1109/ISIT45174.2021.9517884
M3 - Conference contribution
AN - SCOPUS:85115044970
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 599
EP - 604
BT - 2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Symposium on Information Theory, ISIT 2021
Y2 - 12 July 2021 through 20 July 2021
ER -