Energy-Efficient Cluster-based Routing in Multimedia assisted Wireless Sensor Networks Using Resilient Honey Badger Optimization Algorithm

Clustering and routing are effective solutions for addressing the potential design difficulty of energy efficiency in multimedia-assisted Wireless Sensor Networks (WSNs). However, imbalances in the distribution of chosen Cluster Head (CH) nodes and difficult data transmission routes might lead to unequal energy exhaustion in the network. This work focuses on Energy-Efficient Cluster-based Routing Protocols using the Resilient Honey Badger Optimization Algorithm (EECR-RHBOA) for Cluster Head (CH) selection in WSN. Inspired by honey badger foraging behaviour, the RHBOA algorithm incorporates resilience and adaptation into cluster formation and routing selections to guarantee optimum network energy usage. RHBOA selects the best cluster head among all the sensors regarding distance to the residual energy, Base Stations (BS), distance to neighbours, node degree, and centrality. The two main steps of the suggested EECR protocol are cluster formation and data transmission. The RHBOA algorithm arranges sensor nodes into clusters during the cluster formation phase. The method then examines a fitness function considering residual energy, node centrality, and intra-cluster communication cost to choose cluster heads. Extended network lifespan is achieved by reaching balanced energy consumption among multiple nodes. The RHBOA algorithm minimizes energy dissipation during data transmission by optimizing multi-hop routing processes from CHs to BS. These approaches avoid nodes with low energy and help alleviate network congestion. The numerical outcomes show the suggested EECR-RHBOA technique to achieve a lower packet ratio of 0.05, throughput of 104Kbps, packet delivery ratio of 96.2% and coverage rate of 94.8% compared to other methods.