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  1. Pubblicazioni

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

Capitolo di libro
Data di Pubblicazione:
2013
Citazione:
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]
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.
Tipologia CRIS:
Capitolo/Saggio
Keywords:
Auto-localization; Particle Swarm Optimization; Maximum-Likelihood Algorithms
Elenco autori:
Monica, S.; Ferrari, G.
Autori di Ateneo:
MONICA Stefania
Link alla scheda completa:
https://iris.unimore.it/handle/11380/1207004
Titolo del libro:
Adaptive and Natural Computing Algorithms, Lecture Notes in Computer Science Volume 7824
Pubblicato in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
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URL

http://link.springer.com/chapter/10.1007%2F978-3-642-37213-1_47#
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