A Computationally Efficient Algorithm for Quickest Change Detection in Anonymous Heterogeneous Sensor Networks

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 distribut...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2021 IEEE International Symposium on Information Theory (ISIT) s. 599 - 604
Hlavní autori: Sun, Zhongchang, Li, Qunwei, Zhang, Ruizhi, Zou, Shaofeng
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 12.07.2021
Predmet:
Approximation algorithms
Change detection algorithms
Computational efficiency
Information theory
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
DOI:10.1109/ISIT45174.2021.9517884