Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
IEEE Transactions on Computers
Locally constructed algorithms for distributed computations in ad-hoc networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
On Distributed Fault-Tolerant Detection in Wireless Sensor Networks
IEEE Transactions on Computers
A scheme for robust distributed sensor fusion based on average consensus
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Distributed fault detection of wireless sensor networks
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Boundary estimation in sensor networks: theory and methods
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
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In wireless sensor networks, faulty sensors may produce incorrect data and transmit the data to other sensors. They may cause inappropriate data fusion. Furthermore, they would consume the limited energy and bandwidth of sensor networks. In this paper, we propose a distributed faulty sensor detection scheme, in which we assume that the sensor fault probability or reliability is unknown and data to be sensed has Gaussian distribution with unknown parameters. In the proposed method, each sensor obtains a global convergency data through data fusion and makes a local 3-level decision by hypothesis testing against the global convergency data. A final decision about the sensor is then obtained by fusing the decisions of its neighbors. The detection is carried out in a distributed fashion as each sensor only communicates with its neighbors in the entire process. Experiment results demonstrate that the proposed algorithm is able to achieve higher detection accuracy than existing methods even without the knowledge of sensor reliability and parameters of data distribution.