Clustering solutions and analysis for cognitive radio Wireless Sensor Networks

Cognitive radio Wireless Sensor Network is one of the emerging technologies to address the challenges of conventional wireless networks. The core functionality of any network like Mobile Ad hoc Network (MANET), Wireless Sensor Network (WSN), etc., is based on the routing mechanism. For CR-WSNs, three types of routing schemes are used such as multihop routing, one-hop routing, and cluster-based routing. Because of the potential for impractical methods with the one-hop routing and the latency correlated with the multihop routing, the cluster-based routing is considered encouraging. Thus clusteringbased solutions received more attention for WSNs and CR-WSNs than other routing strategies. While working with CR-WSNs, the primary constraints are limited processing power and sensor nodes, and hence it is necessary to consider energy-efficient clustering design to enhance the network lifetime. Several clustering solutions are proposed for WSNs. However, it is noticed that clustering methods of WSNs cannot directly be applied to CR-WSNs due to topology variations. Designing the clustering protocol for CR-WSNs is a challenging problem compared to WSN. This article briefly reviews the current clustering protocols in CRSN and performs a comparative performance analysis on some of these protocols. The experimental results are derived through simulation, and the results are plotted for performance parameters such as throughput, packet delivery rate (PDR), overhead, energy consumption, and delay. The paper concludes by focusing on the standard protocols' performance variations.