Advancing Cloud Gaming: Addressing Latency Challenges through Research and Innovative Solutions

Cloud gaming is changing the gaming industry by offering high-quality gameplay without needing powerful local hardware. However, common problems like high lag, network congestion, and inconsistent Quality of Experience (QoE) limit its broader use. This document addresses these challenges through an in-depth analysis of a large-scale latency dataset gathered from 189 players interacting with 9 servers across North America, South America, Europe, and East Asia. Utilizing several models, such as Random Forest, Gradient Boosting, and Linear Regression, we predict latency patterns and identify the elements influencing performance declines. Our results reveal significant regional variations in server performance and show that cloud gaming performance may be significantly enhanced by hybrid configurations that include the best features of both platforms, such as adaptive Quality of Experience (QoE) models and local computation through edge nodes. Three key contributions are provided by this research: (1) a data-driven model for predicting latency in global cloud gaming networks; (2) a detailed analysis of leading platforms to ascertain their advantages and drawbacks; and (3) the proposal of a novel hybrid framework based on data-driven resource allocation techniques. These contributions lay the groundwork for improving user experience across a range of network configurations and optimizing cloud gaming systems.