Cloud gaming platforms lower the access barriers to graphics-intensive games by rendering computationally heavy game scenes on cloud GPU servers and streaming them back to players as real-time video, which in turn places significant demands on carrier networks to deliver these video streams with high throughput, low latency and minimal packet loss. To achieve decent user experience, cloud gaming platforms adapt streaming behaviors based on network conditions and allow users to adjust their graphics settings. Knowing the level of game streaming adaptability offered by various cloud gaming providers is helpful for network operators to effectively provision network resources for subscriber satisfaction, and for game development community to incentivize cloud gaming providers to better optimize their streaming techniques. Toward this objective, we develop a systematic framework to assess the adaptability of a cloud gaming platform in reducing network demand for lower client graphics settings; and in adjusting streaming quality under constrained network conditions for smooth gaming experience. Focusing on four popular platforms (NVIDIA GFN, Xbox, PlayStation and Amazon Luna), we begin by empirically profiling and comparing how they adapt game streaming characteristics to various levels of client graphics settings and network conditions. Building on the insights, we develop our systematic assessment framework, which provides quantitative scores for both fine-grained metrics by processing labeled traffic traces, as well as aggregated scores tailored to an assessor’s preference. We showcase our quantitative assessments of the four platforms.
Lyu et al. (Sun,) studied this question.