WaAOA_DenseNet: Walrus Archimedes Optimization Algorithm‐Based Trust Updation in UAV‐Assisted Wireless Sensor Network

ABSTRACT Unmanned aerial vehicles (UAVs) have appeared as a remarkable solution for data gathering of huge‐scale wireless sensor networks (WSNs). It is utilized as a sink node to accumulate data from sensor nodes. Also, it assists the network in extending its life span and eliminates the energy‐hole issue experienced by sensor networks. The most important need is the timely collection of data from sensor nodes and to broadcast the data to the base station. The safest path is the basic line for efficient operations, and it is a significant and more complex thing to determine the effective route in an environment by compromising different hurdles and guaranteeing that the route can effectively achieve the target point. This research addresses the clustering problem and updates the trust level of nodes using the proposed Walrus Archimedes optimization algorithm (WaAOA)_DenseNet. More specifically, the trust updation is done utilizing DenseNet, and it is optimally tuned based on the proposed algorithm, which is an incorporation of the Walrus optimization algorithm (WOA) and Archimedes optimization algorithm (AOA).