Hybrid optimization-based secured routing in mobile ad-hoc network

Abstract

Mobile Ad hoc Networks (MANETs) pose significant routing challenges due to their decentralized and dynamic nature. Node mobility results in frequent changes in network topology, leading to unsFIG connectivity and link quality. Traditional RPs designed for static networks are inadequate for MANETs. To deal with these issues, a secure routing approach is proposed using the Red Panda-Lyrebrid Optimization (RePLO) algorithm, which combines the advantages of the Red Panda Optimization (RPO) and Lyrebird Optimization Algorithm (LOA) algorithms. The proposed approach consists of five steps: (i) configuring the system model, (ii) developing the energy model, (iii) creating the mobility model, (iv) selecting cluster heads using the RePLO algorithm, and (v) routing using the RePLO algorithm. The RePLO algorithm optimizes cluster head selection and routing while considering specific constraints such as delay, distance, energy, & security for Cluster Head (CH) selection, and link quality and enhanced trust for routing optimization. The effectiveness of the proposed approach is evaluated using various metrics to demonstrate its efficiency in MANET routing. By integrating multiple optimization techniques and considering critical constraints, the RePLO algorithm offers a systematic and secure solution for MANET routing. The evaluation results confirm the efficacy of the proposed approach in improving network performance, reliability, and security. Overall, the RePLO algorithm presents a promising approach to tackle the routing issues inherent in MANETs, paving the way for more robust and efficient communication in mobile ad hoc networks.