MANETs and WSNs in Hybrid Genghis Khan Shark and Lotus Effect Optimizer for Secure Routing

ABSTRACT Mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs) face significant challenges due to dynamic topology, limited energy resources, and security threats. This work presents a hybrid Genghis Khan shark–lotus effect optimizer (GKS‐LEO) for trust‐aware, energy‐efficient, and secure routing. Soft k ‐mean clustering and a crayfish optimization algorithm enable stable cluster formation and adaptive cluster head selection, while a deep squeeze multichannel attention network evaluates hop quality using trust, energy, and link features. Simulation results demonstrate that GKS‐LEO achieves a 99% packet delivery ratio (PDR) and reduces energy consumption to 0.5 mJ, outperforming traditional approaches by up to 30% in network longevity. These results validate the proposed model's capability to balance security, trust, and efficiency, making it suitable for deployment in mission‐critical and resource‐constrained environments. Future work will extend this framework with blockchain‐enabled trust management and SDN‐based control for enhanced scalability.