The thesis focuses on deploying an software-defined wide area network (SD-WAN) featuring LTE, MPLS, and Satellite tunnels. Using the Proximal Policy Optimization (PPO) algorithm in reinforcement learning, the study aims to enhance network performance by minimizing delays. The simulation, conducted with Python and Mininet, assesses the ability to intelligently select optimal links based on criteria such as bandwidth and delay satisfaction