Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
Localization from Connectivity in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
A hub matrix theory and applications to wireless communications
EURASIP Journal on Applied Signal Processing
A decentralized algorithm for spectral analysis
Journal of Computer and System Sciences
Localization with snap-inducing shaped residuals (SISR): coping with errors in measurement
Proceedings of the 15th annual international conference on Mobile computing and networking
Validating sensors in the field via spectral clustering based on their measurement data
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
An energy-efficient adaptive clustering algorithm with load balancing for wireless sensor network
International Journal of Sensor Networks
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In a distributed sensor network, the goodness of a sensor may change according to its current device status (e.g. health of hardware) and environment (e.g. wireless reception conditions at the sensor location). As a result, it is often necessary to validate periodically sensors in the field, in order to identify those which no longer work properly and eliminate them from applications' use. In this paper, we describe a spectral clustering approach of using peer sensors to identify these bad sensors. Using a simple model problem, we describe how our sensor validation method works and demonstrate its performance in simulation.