Enhancing Wireless Mesh Network Performance Through AI-Based Routing Algorithms

Wireless Mesh Networks (WMNs) are critical in ensuring ubiquitous internet coverage, particularly in environments and terrains with unique challenges. The increasing number of wireless devices and services has created a critical need for routing techniques that are more efficient and adaptable. Although conventional routing algorithms exhibit resilience, they frequently remain fixed and fail to adapt to swift fluctuations in network circumstances. By incorporating Artificial Intelligence (AI)-based routing algorithms, this article proposes a novel method for improving the efficacy of WMNs. We present an innovative AI-driven routing algorithm that dynamically adapts to fluctuating network conditions by leveraging reinforcement learning and deep learning techniques. Our methodology considers various elements, including interference, node dependability, bandwidth consumption, and node mobility. In contrast to conventional approaches, the algorithm powered by artificial intelligence perpetually acquires knowledge from its surroundings, forecasting possible breakdowns or congestion, and subsequently redirects data packets along a more efficient trajectory. Experiments performed on simulated and real-world WMN scenarios revealed significant enhancements in packet delivery ratio, latency, and throughput compared to traditional routing methods. In addition, our AI model's adaptability guarantees the network's resistance to external disturbances and its capacity to expand to accommodate an increasing number of nodes. The study's results highlight the capacity of artificial intelligence to fundamentally transform the domain of wireless networking. Incorporating intelligent algorithms into wide-area networks (WMNs) infrastructure can guarantee end-users a more streamlined, effective, and resilient internet experience. Further investigations are warranted to determine whether the proposed method can be implemented in alternative wireless architectures and to enhance the algorithm by utilizing hybrid AI techniques.