A Large-Scale Network Measurement Study of NVIDIA GeForce NOW Cloud Gaming in the Wild

Cloud gaming, whereby game graphics is rendered in cloud servers and streamed back to the user, expands the gaming market to billions of users who do not have gaming consoles or high-power graphics PCs. However, cloud gaming puts high pressure on the access network operator to provide stable and high-bandwidth network connectivity (often an order of magnitude more than console gaming) so users can have a good gaming experience. This paper aims to help network operators gain visibility into cloud gaming behaviors and experience, so they can better plan for it and manage it. We focus specifically on NVIDIA’s GeForce NOW cloud gaming platform, and make four contributions. First, we comprehensively analyze the network anatomy of the cloud gaming session, including establishment of flows and their volumetric patterns, and illustrate differences across user setups. Second, we develop a method to detect cloud gaming activity and user setup in real-time, as well as quantify user experience in terms of frame rate, resolution, and latency. In our third contribution we deploy our algorithm in a campus network and reveal insights on user setups (PC versus mobile, browser versus app) and experience (frames-per-second and resolution) of gameplay sessions detected over four months. For our final contribution we measure cloud gaming at scale in the wild by deploying our solution in a commercial operator of NVIDIA’s GeForce NOW platform, and show how experience relates to user setup, game title, access network type and subnet.