optimization techniques for cluster based routing in cognitive radio sensor neworks for 5G 6G applications

Abstract

Cognitive Radio Wireless Sensor Networks (CR-WSNs) are a promising solution to wireless network dependability issues. Routing is the foundation of any network, including WSNs and Mobile Ad Hoc Networks (MANETs). CR-WSNs employ multi-hop, one-hop, and cluster-based routing. Cluster-based routing is promising due to the impracticality of one-hop routing and the latency of multi-hop routing. Thus, clustering-based routing algorithms were prioritized for WSNs and CR-WSNs. In CR-WSNs, sensor nodes have limited processing power and capabilities, therefore energy-efficient clustering architecture is needed to extend the network lifetime. Several WSN clustering solutions exist, however, topological changes prevent them from being used for CR-WSNs. To address the shortcomings of previous CR-WSN clustering methods, novel Artificial intelligence (AI)-based clustering solutions for CR-WSNs have been developed. In the first contribution, optimization techniques for improving CR-WSN routing in a clustering setting were examined. CR-WSN clustering-based protocols were developed using two optimization techniques: Ant Colony Optimisation (ACO) and Artificial Bee Colony (ABC). ABC-based Clustering (ABCC) was an ABC-based protocol, whereas ACO-based Modified Threshold-sensitive Energy Efficient Network (ATEEN) was also an ACO-based protocol. Both the ABCC and ATEEN AI-based protocols were designed to handle clustering issues in CR-WSNs, such as Secondary User connection, ensuring Primary User (PU) security, cluster number, inefficient spectrum sharing, and proper Cluster Head (CH) selection. We presented Dynamic Fuzzy-based PU aware Clustering (DFPC) for CR-WSNs in the second contribution of this thesis. The DFPC is divided into parts that include a dynamic technique for determining the number of clusters, a fuzzy-based algorithm for optimal CH selection, and reliable multi-hop data transfer to assure PU security. To improve the performance of the CR-WSNs, an efficient technique was devised to determine the optimal number of cluste