Recently, cognitive wireless sensor networks (CWSN) have been proposed to enhance the overall functionality of WSNs based on application needs. Cognition refers to the process of making decisions and acting based on the network conditions in order to achieve end-to-end goals of the network. In the previously proposed architecture, a new node — Cognitive Node (CN)-, which is responsible for managing the network, was introduced to the network. Since WSNs normally consist of a huge number of Sensor Nodes (SNs), there is a high demand to have more than one CN. In this paper, challenges of adding multiple CNs are investigated and a new architecture is proposed. Then, the proposed architecture is evaluated by implementing it with CC2430 boards (Texas Instrument boards). The results of our experiments showed that the proposed architecture can function more efficiently by increasing the number of SNs in each subclass.
