An optimal ant colony algorithm based on security-aware distributed fuzzy logic to increase data rate and reduce latency in 5G mobile ad hoc networks
Abstract The advent of 5G communication plays a crucial role in today's evolving technology landscape. 5G Mobile Ad-hoc Networks (MANETs) drive a wireless system characterized by extremely high data rates, low power consumption, and minimal time and cost. Consequently, routing protocols for MANETs must be inherently flexible, high-performing, and energy-efficient. The primary goal of 5G communication is to offer significantly higher data rates and remarkably low over-the-air latency. This research describes a novel routing protocol developed for MANETs using a bio-inspired technique. Biology-inspired algorithms incorporate routing capabilities derived from the social behavior of ant colonies, bird flocks, bee dances, and similar phenomena, promising to effectively address the challenges inherent in MANETs. Some of these challenges include limited bandwidth, constrained battery life, low memory capacity, and others. Therefore, this study proposes a novel Security-Aware Distributed Fuzzy Logic-based Optimized Ant Colony Algorithm (ACO) designed to enhance the data rate and reduce latency in 5G MANETs. The objective is to develop a MANET routing protocol capable of achieving a stable packet delivery ratio, lower connection overhead, and low end-to-end delay across standard operational scenarios and under attack modes. The proposed algorithm is analyzed based on various performance metrics, including throughput, latency, packet loss, network lifetime, and others, demonstrating effective results through a hybrid architecture. Keywords: Mobile Ad-hoc Networks (MANETs), Distributed Fuzzy Logic, Security, Ant Colony Optimization (ACO), End-to-End Delay, Data Rate, Routing.