Dissecting Cloud Gaming Performance with DECAF

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Abstract

Cloud gaming platforms have witnessed tremendous growth over the past two years, with a number of large Internet companies including Amazon, Facebook, Google, Microsoft, and Nvidia publicly launching their own platforms. However, there is an absence of systematic performance measurement methodologies which can generally be applied. In this paper, we implement DECAF, a methodology to systematically analyze and dissect the performance of cloud gaming platforms across different game genres and game platforms. By applying DECAF, we measure the performance of Google Stadia, Amazon Luna, and Nvidia GeForceNow, and uncover a number of important findings such as processing delays in the cloud comprise majority of the total round trip delay (≈73.54%), the video streams delivered by these platforms are characterized by high variability of bitrate, frame rate, and resolution. Our work has important implications for cloud gaming platforms and opens the door for further research on measurement methodologies for cloud gaming.

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APA

Iqbal, H., Khalid, A., & Shahzad, M. (2022). Dissecting Cloud Gaming Performance with DECAF. In Performance Evaluation Review (Vol. 50, pp. 13–14). Association for Computing Machinery. https://doi.org/10.1145/3489048.3522628

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