Enhancing Throughput in Mobile Ad Hoc Networks Through Ant Colony Optimization Integration

Mobile Ad Hoc Networks (MANETs) represent a dynamic and self-configuring network paradigm where nodes communicate without a fixed infrastructure. This paper provides a succinct yet comprehensive exploration of MANETs and their distinctive characteristics, emphasizing the challenges associated with routing in such decentralized environments. In parallel, the paper introduces Ant Colony Optimization (ACO), a nature-inspired algorithm known for its prowess in solving optimization problems through the simulation of ant foraging behavior. The paper summarizes key findings stemming from an in-depth exploration of ACO's applicability in the context of MANETs. Through a critical analysis of existing literature, the research identifies opportunities for synergy between ACO and MANETs, showcasing the potential improvements in routing performance. The impacts of the presented work lie in advising a novel mixing technique that weights the ability of the ACO to adjust by altering the network conditions and by optimizing the decisions of routing strategy. The fusion of Ant Colony Optimization into Mobile Ad Hoc Networks presents a favorable road path for gripping the inherited contests inherent that lie in the distributed communication. By exploiting the ethics of swarm intelligence, this research paper encourages an adaptive, robust, and efficient framework for routing in MANET by offering the better throughput in the experiments.