Fuzzy Clustering for Next Generation Wireless Sensor Networks

Ola Albeshri, Laila Nassef, Etimad Fadel


The massive growing demands for radio wireless communications have resulted in a spectrum scarcity problem. Cognitive radios utilize a dynamic spectrum access to share the spectrum with licensed frequency bands in an opportunistic manner. The integration of cognitive radio with wireless sensor nodes can improve spectrum utilization and increase communication quality. Currently, clustering protocols have been developed to minimize energy consumption and to prolong network’s lifetime. However, spectrum awareness in not considered. Thus, clustering protocols need to adapt to the changes in the surrounding environment and to optimally consider both energy efficiency and spectrum awareness. Therefore, this paper develops a fuzzy based energy efficient and spectrum aware clustering protocol (FEESA) to optimally elect cluster heads based on four conflicting parameters: residual energy, distance to base station, node degree, and channel availability. The performance of the proposed protocol is simulated using MATLAB and Mamdani fussy inference system. Two simulation scenarios and three performance metrics were used. The proposed fussy clustering protocol is compared with three different protocols: a basic energy efficient protocol, a spectrum aware protocol, and an energy efficient spectrum aware protocol which uses a weighting function. The simulation results indicate the effectiveness of the proposed fuzzy based clustering protocol to extend network lifetime and reduce energy consumption.


Routing Protocols, Cognitive Radio Sensor Networks, Spectrum Aware, Fuzzy Logic


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