Simultaneous node distribution in a cognitive radio network

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.