Abstract
Wireless sensor networks (WSNs) are one of the most widely recognized dynamic systems used for monitoring and tracking. Cognitive radio technology has been incorporated into wireless sensors to meet the frequency requirements of WSN-based systems such as the Internet of Things (IoT) and vehicular networks. As a matter of fact, data routing has a great impact on self-organized networks. We therefore introduce a cognitive dynamic low energy adaptive clustering hierarchy (CDLEACH) protocol dedicated to cognitive WSNs. CDLEACH is based on a dynamic cognitive clustering approach. In fact, the number of cluster heads (CH) should be adjusted over the network lifetime based on the number of alive sensor nodes (SNs). In addition, SNs with the highest observed idle channels are selected as CHs. In order to test the proposed data routing algorithm under realistic circumstances, we derive the analytical energy model in which the energy-sensing range of the consumed SNs is taken into account. The simulation results show that CDLEACH provides a significant reduction of the energy consumption of SNs. Consequently, a good enhancement in terms of network lifetime is shown in addition to an increase of the amount of transmitted data.