Design of a System For QoS1 Optimizing And Load Balancing In Wi-Fi Networks Using The Ryu Controller In Software-Defined Network

Abstract

The growing demand for connectivity, combined with the exponential increase in data traffic, presents significant challenges for WiFi networks, particularly in managing quality of service and load balancing. These issues are further intensified by technological advancements and the integration of systems such as Artificial Intelligence and the Internet of Things, which generate data volumes that current infrastructures struggle to handle efficiently. To address this, the project proposes designing a system based on an SDN environment that, using the Ryu controller, integrates QoS and load balancing algorithms supported by machine learning techniques. The methodology involves analysis, design, implementation, evaluation, and optimization through simulations and testing in various scenarios. The system is expected to improve traffic distribution, reduce latency and packet loss, and optimize other network resources, ensuring a better user experience and greater operational efficiency amid growing demands. In conclusion, the proposed solution tackles current congestion and overload issues in WiFi networks with an SDN and machine learning-based approach, providing an efficient and scalable alternative to enhance the performance of modern networks.