Quickest Change Detection In Anonymous Heterogeneous Sensor Networks
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 oc...
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| Veröffentlicht in: | Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) S. 5925 - 5929 |
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01.05.2020
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| Abstract | 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]. |
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| AbstractList | 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]. |
| Author | Li, Qunwei Sun, Zhongchang Zou, Shaofeng |
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| Snippet | The problem of quickest change detection (QCD) in anonymous heterogeneous sensor networks is studied. There are n heterogeneous sensors and a fusion center.... |
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| SubjectTerms | Anonymous Change detection algorithms Computational efficiency Conferences heterogeneous hypothesis testing mixture CuSum sequential change detection Signal processing Signal processing algorithms Speech processing Testing |
| Title | Quickest Change Detection In Anonymous Heterogeneous Sensor Networks |
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