FJSO-Based Optimized Multipath Routing in Mobile Ad-Hoc Networks

Abstract

Mobile Ad Hoc Networks (MANETs) are characterized by dynamic topologies and decentralized architecture, posing significant challenges for stable and energy-efficient routing. This paper presents a Fractional Jellyfish Search Optimization (FJSO)–based routing framework that efficiently balances exploration and exploitation during route discovery. The FJSO algorithm introduces fractional-order adaptively, enhancing convergence and robustness against link failures. The proposed method optimizes multipath routing by adaptively learning the best communication paths based on energy, mobility, and stability metrics. Simulation results demonstrate that the FJSO-based routing approach outperforms existing protocols in terms of path maintenance efficiency, energy consumption, network lifetime, packet delivery ratio (PDR), and throughput, confirming its suitability for large-scale and highly dynamic MANET environments.