Quality of Service Prediction

Quality of Service (QoS) prediction aims to forecast the performance of services, enabling proactive resource allocation and improved user experience. Current research heavily utilizes machine learning, focusing on advanced architectures like graph convolutional networks, tensor factorization methods (including variations incorporating beta-divergence and ADMM optimization), and large language models to capture complex spatiotemporal relationships and user-service interactions within often sparse and noisy datasets. These advancements are crucial for optimizing service recommendations, enhancing network performance in areas like vehicular communication and teleoperated driving, and ensuring privacy-preserving data analysis in distributed environments.