In this paper, the problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. Aiming at an efficient resource exploitation, the research adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimise the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. We consider the computation of the Posterior Cramér-Rao Bound (PCRB) on the tracking accuracy based on Received Signal Strength (RSS) measurements. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented one, both in the centralised and in the distributed manner. Their performances are compared through simulation with the theoretical lower PCRB. The node selection problem is formulated as a crosslayer energy minimisation problem, whose solution is addressed by a greedy-type algorithm, both in the static scenario and in the dynamic scenario. Copyright © 2011 Inderscience Enterprises Ltd.

Energy-efficient collaborative tracking in wireless sensor networks

LONGO, Maurizio
2011-01-01

Abstract

In this paper, the problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. Aiming at an efficient resource exploitation, the research adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimise the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. We consider the computation of the Posterior Cramér-Rao Bound (PCRB) on the tracking accuracy based on Received Signal Strength (RSS) measurements. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented one, both in the centralised and in the distributed manner. Their performances are compared through simulation with the theoretical lower PCRB. The node selection problem is formulated as a crosslayer energy minimisation problem, whose solution is addressed by a greedy-type algorithm, both in the static scenario and in the dynamic scenario. Copyright © 2011 Inderscience Enterprises Ltd.
2011
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4672662
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