Spectrum aware fuzzy clustering algorithm for cognative radio sensor networks
This paper proposes a SAFCA for a self-organized CH selection within a CRSN. The
algorithm caters CR and WSN constraints by exploiting the dynamic spectrum access and
fuzzy inference technique for an energy efficient CRSN. It utilizes channel availability and
fuzzy parameters of residual energy, communication cost and node distribution. The
simulation measure the significant of the selected parameters. The first stage investigates the
impact of inclusion of fuzzy inference towards the channel availability in the clustering
algorithm, meanwhile the second stage explores the significant of the fuzzy parameters. The
performance metric of network stability i.e. FND and network lifetime i.e.HNA are measured to determine the energy efficiency of the clustering algorithm. The results show the algorithm outperforms SACA, SAFEC, SAFEN and SAFCN of FND, HNA, number of alive nodes and energy consumption.
Keywords: cognitive radio; wireless sensor node; clustering; channel availability; fuzzy.