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Dissecting Cloud Gaming Performance with DECAF

Published: 06 June 2022 Publication History

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.

References

[1]
2021. DECAF: Dissecting Cloud Gaming Performace. https://github.com/decafCG/decaf.
[2]
Te-Yuan Huang, Nikhil Handigol, Brandon Heller, Nick McKeown, and Ramesh Johari. 2012. Confused, Timid, and Unstable: Picking a Video Streaming Rate is Hard (ACM IMC'12).
[3]
Hassan Iqbal, Ayesha Khalid, and Muhammad Shahzad. 2021. Dissecting Cloud Gaming Performance with DECAF. ACM POMACS'21.

Cited By

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  • (2024)Network Anatomy and Real-Time Measurement of Nvidia GeForce NOW Cloud GamingPassive and Active Measurement10.1007/978-3-031-56249-5_3(61-91)Online publication date: 11-Mar-2024

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      Published In

      cover image ACM Conferences
      SIGMETRICS/PERFORMANCE '22: Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems
      June 2022
      132 pages
      ISBN:9781450391412
      DOI:10.1145/3489048
      • cover image ACM SIGMETRICS Performance Evaluation Review
        ACM SIGMETRICS Performance Evaluation Review  Volume 50, Issue 1
        SIGMETRICS '22
        June 2022
        118 pages
        ISSN:0163-5999
        DOI:10.1145/3547353
        Issue’s Table of Contents
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 06 June 2022

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      Author Tags

      1. cloud gaming
      2. deep learning
      3. game bot
      4. latency
      5. measurement
      6. network utilization
      7. performance evaluation
      8. streaming bitrate

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      SIGMETRICS/PERFORMANCE '22
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      Overall Acceptance Rate 459 of 2,691 submissions, 17%

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      Cited By

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      • (2024)Network Anatomy and Real-Time Measurement of Nvidia GeForce NOW Cloud GamingPassive and Active Measurement10.1007/978-3-031-56249-5_3(61-91)Online publication date: 11-Mar-2024

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