Energy and Trust Aware Cluster-Based Routing in WSN via Self-Improved Beluga Whale Optimization

The other sensor nodes in the cluster are sending their detected data to the CH, which is aggregating and sending it to the BS. A cluster head is considered to have greater capability and energy than other sensor nodes. The cluster head also reduces energy usage and provides scalability for large node counts. Yet, selecting the optimum CH is difficult since it has the greatest influence on the network's energy usage. In order to maximize secure and energy-aware routing in wireless sensor networks, this research presents a novel cluster-based routing model with optimal CHS. The best CH will be selected in the present investigation depending on the requirements as follows: distance, security (risk level evaluation), distance, delay, energy, and trust evaluation (direct and indirect trust). The routing model also considers how the route quality (reliability) of a cluster is calculated. This work proposes a new self-adaptive Beluga whale optimization method (SABWO) that uses it as the optimization issue. Finally, the findings of simulations confirm the effectiveness of the proposed strategy with respect to delay, throughput, residual energy, etc.