Traffic Steering

Traffic steering optimizes network resource allocation by intelligently directing data traffic across different network paths and radio access technologies to minimize latency, maximize throughput, and improve overall quality of service. Current research heavily focuses on leveraging machine learning, particularly reinforcement learning and deep learning models (like convolutional neural networks and Q-learning), within open radio access network (O-RAN) architectures to achieve adaptive and efficient traffic control. This work is significant for enabling the development of self-optimizing and programmable networks, ultimately improving the performance and user experience of 5G and beyond networks.