Simultaneous node distribution in a cognitive radio network - BENADLA, Sarra
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In this project, we present a parallel version of the k-nearest neighbor (k-ppv) algorithm. The aim is to optimize the allocation of radio nodes in a cognitive radio network already structured in clusters. We adopted a multi-agent modeling approach and selected the JADE multi-agent platform for our simulations. The results obtained are promising, with a reduction in execution time of around 50% compared with the basic sequential algorithm.

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Produktbeschreibung
In this project, we present a parallel version of the k-nearest neighbor (k-ppv) algorithm. The aim is to optimize the allocation of radio nodes in a cognitive radio network already structured in clusters. We adopted a multi-agent modeling approach and selected the JADE multi-agent platform for our simulations. The results obtained are promising, with a reduction in execution time of around 50% compared with the basic sequential algorithm.
Autorenporträt
Dr. Benadla Sarra possui doutorado em Computação Distribuída e Redes pela Universidade de Tlemcen. A sua investigação centra-se em redes de rádio cognitivas, paralelamente, interessa-se pela segurança de redes, em particular a utilização de blockchain para reforçar a proteção de sistemas e dados.