Measurement of the responses of cloud-based game streaming to network congestion

Cloud-based game streaming has emerged as a viable way to play games anywhere with a good network connection. While previous research has studied the network turbulence of game streaming traffic, there is as of yet no work exploring how cloud-based game streaming responds to rival connections on a congested network. This paper presents experiments measuring and comparing the network response for three popular commercial streaming services - Google Stadia, NVidia GeForce Now, and Amazon Luna - competing with TCP flows on a congested network. Analysis of the bitrates, loss and latency show that the three systems have different adaptations to network congestion and vary in their fairness to competing TCP flows sharing a bottleneck link.

[1]  B. Bellalta,et al.  Cloud-gaming: Analysis of Google Stadia traffic , 2020, Comput. Commun..

[2]  Olivier Festor,et al.  An Analysis of Cloud Gaming Platforms Behavior under Different Network Constraints , 2021, 2021 17th International Conference on Network and Service Management (CNSM).

[3]  Mark Claypool,et al.  A First Look at the Network Turbulence for Google Stadia Cloud-based Game Streaming , 2021, IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[4]  Luca Vassio,et al.  A network analysis on cloud gaming: Stadia, GeForce Now and PSNow , 2020, Network.

[5]  M. Claypool,et al.  Sharing but not Caring – Performance of TCP BBR and TCP CUBIC at the Network Bottleneck , 2019 .

[6]  Toke Høiland-Jørgensen,et al.  The Flow Queue CoDel Packet Scheduler and Active Queue Management Algorithm , 2018, RFC.

[7]  N. Cardwell,et al.  BBR , 2017, CACM.

[8]  Van Jacobson,et al.  BBR: Congestion-Based Congestion Control , 2016, ACM Queue.

[9]  Lea Skorin-Kapov,et al.  Analysis and QoE evaluation of cloud gaming service adaptation under different network conditions: The case of NVIDIA GeForce NOW , 2016, 2016 Eighth International Conference on Quality of Multimedia Experience (QoMEX).

[10]  Cheng-Hsin Hsu,et al.  On the Quality of Service of Cloud Gaming Systems , 2014, IEEE Transactions on Multimedia.

[11]  Mahmoud Reza Hashemi,et al.  Efficient bitrate reduction using a Game Attention Model in cloud gaming , 2013, 2013 IEEE International Symposium on Haptic Audio Visual Environments and Games (HAVE).

[12]  José Alberto Hernández,et al.  An empirical study of Cloud Gaming , 2012, 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames).

[13]  Mark Claypool,et al.  Thin to win? Network performance analysis of the OnLive thin client game system , 2012, 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames).

[14]  J Gettys,et al.  Bufferbloat: Dark Buffers in the Internet , 2011, IEEE Internet Computing.

[15]  Injong Rhee,et al.  CUBIC: a new TCP-friendly high-speed TCP variant , 2008, OPSR.