Optimizing Manet Routing in Iot with Antlion Grey Wolf Hybrid Approach Enhancing Energy Efficiency, Trust, Stability, and Bandwidth

Abstract

Wireless Sensor Networks (WSN) act as a vital link between the physical and information networks in the Internet of Things (IoT). Energy efficiency and trustworthiness are key factors in ensuring reliable communication in these networks. During multicast routing, the Base Station (BS) is responsible for securely transmitting data to multiple destinations via intermediate nodes, which is a significant challenge in IoT and Mobile Ad-hoc Networks (MANET). An energy-conscious multicast routing system that combines Antlion Optimization (ALO) and Grey Wolf Optimization (GWO) is presented in this paper: the Antlion Grey Wolf Energy-Trust Pathway (ALGWO-ETP). It makes use of an objective function that assesses bandwidth, energy, trust, and link stability. In order to guarantee safe and effective node selection, routes are created and optimized using these parameters, with energy and trust levels updated following each transmission. To further enhance security and routing efficiency, the protocol is augmented with the Improved Salp Swarm Algorithm (ISSA) and Elliptic-curve Cryptography (ECC). The ISSA evaluates and selects the most secure and efficient multiple paths, optimizing routing decisions based on node energy and trustworthiness. Meanwhile, the ECC mechanism secures data transmission by validating node keys and shared codes, ensuring that only legitimate nodes participate in the network. This process enhances communication reliability and efficiency in the network. The proposed model was evaluated through extensive simulations in MATLAB, comparing its performance against existing techniques. The simulations, conducted with networks of 50 and 100 nodes, demonstrated significant improvements in minimal delay, maximum detection rate, energy efficiency, bandwidth utilization, and throughput.