In this paper, we consider the problem of auto-localization of the nodes of a static Wireless Sensor Network (WSN) where nodes communicate through Ultra Wide Band (UWB) signaling. In particular, we investigate auto-localization of the nodes assuming to know the position of a few initial nodes, denoted as “beacons”. In the considered scenario, we compare the location accuracy obtained with the widely used Two-Stage Maximum-Likelihood algorithm with that achieved with an algorithm based on Particle Swarming Optimization (PSO). Accurate simulation results show that the latter can significantly outperform the former.

Particle swarm optimization for auto-localization of nodes in wireless sensor networks / Monica, S.; Ferrari, G.. - 7824:(2013), pp. 456-465. [10.1007/978-3-642-37213-1_47]

Particle swarm optimization for auto-localization of nodes in wireless sensor networks

S. Monica;
2013

Abstract

In this paper, we consider the problem of auto-localization of the nodes of a static Wireless Sensor Network (WSN) where nodes communicate through Ultra Wide Band (UWB) signaling. In particular, we investigate auto-localization of the nodes assuming to know the position of a few initial nodes, denoted as “beacons”. In the considered scenario, we compare the location accuracy obtained with the widely used Two-Stage Maximum-Likelihood algorithm with that achieved with an algorithm based on Particle Swarming Optimization (PSO). Accurate simulation results show that the latter can significantly outperform the former.
2013
Adaptive and Natural Computing Algorithms, Lecture Notes in Computer Science Volume 7824
M Tomassini A. Antonioni F. Daolio P. Buesser
9783642372124
Springer
Particle swarm optimization for auto-localization of nodes in wireless sensor networks / Monica, S.; Ferrari, G.. - 7824:(2013), pp. 456-465. [10.1007/978-3-642-37213-1_47]
Monica, S.; Ferrari, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1207004
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