Secure distance based multi-objective artificial rabbits algorithm for clustering and routing in cognitive radio network

Cognitive radio networks (CRNs) are presently undergoing extensive research and are gaining popularity in a wide range of applications. The nodes in a cognitive radio sensor network have flexibility according to data packets due to dynamic transmission techniques. In this study, the energy consumption within the clustering/routing is taken into account for determining the ideal transmission distance. The cluster size is adjusted depending on the number of packets in the cluster and how the nodes are grouped in a clustered shape. Additionally, due to the cognitive capabilities of the sensor node, it is possible to determine the remaining duration of licensed channels that are not in use in a CRN. Secure distance multi-objective artificial rabbits' algorithm (SD-MOARA) based clustering and routing is utilized to fulfill the extendable efficiency in CRN. The goal of the suggested routing system is to forward data packets along lines that utilize the least amount of energy. The outcomes of the proposed SD-MOARA are examined using MATLAB in terms of the following performances: remaining energy (851.4 J), packet delivery ratio (99.9%), packet loss rate (PLR) (0.2%), energy consumption (23.9 J), throughput (0.99 Mbps), average delay (0.42 s) and routing overhead (0.40). The above-stated results demonstrate that the proposed SD-MOARA outperforms the conventional methods.