Cloud Gaming: Understanding the Support From Advanced Virtualization and Hardware

Existing cloud gaming platforms have mainly focused on private nonvirtualized environments with proprietary hardware. Modern public cloud platforms heavily rely on virtualization for efficient resource sharing, the potentials of which have yet to be explored. Migrating gaming to a public cloud is nontrivial, however, particularly considering the overhead for virtualization and that the graphics processing units (GPUs) for game rendering has long been an obstacle in virtualization. This paper takes a first step toward bridging the online gaming system and the public cloud platforms. We present the design and implementation of a fully virtualized cloud gaming platform with the latest hardware support for both remote servers and local clients. We explore many critical design issues inherent in cloud gaming, including the choice of hardware or software video encoding, and the configuration and the detailed power consumption of thin client. We demonstrate that with the latest hardware and virtualization support, gaming over virtualized cloud can be made possible with careful optimization and integration of the different modules. We also highlight critical challenges toward full-fledged deployment of gaming services over the public virtualized cloud.

[1]  Carlos Reaño,et al.  CU2rCU: Towards the complete rCUDA remote GPU virtualization and sharing solution , 2012, 2012 19th International Conference on High Performance Computing.

[2]  Michael Welzl,et al.  An Evaluation of Tail Loss Recovery Mechanisms for TCP , 2015, CCRV.

[3]  Cheng-Hsin Hsu,et al.  Quantifying User Satisfaction in Mobile Cloud Games , 2014, MoVid@MMSys.

[4]  Han-I Su,et al.  Are all games equally cloud-gaming-friendly? An electromyographic approach , 2012, 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames).

[5]  Alec Wolman,et al.  Demo: DeLorean: using speculation to enable low-latency continuous interaction for mobile cloud gaming , 2014, MobiSys.

[6]  Chao Zhang,et al.  vGASA: Adaptive Scheduling Algorithm of Virtualized GPU Resource in Cloud Gaming , 2014, IEEE Transactions on Parallel and Distributed Systems.

[7]  Gwendal Simon,et al.  The brewing storm in cloud gaming: A measurement study on cloud to end-user latency , 2012, 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames).

[8]  Filip De Turck,et al.  Platform for real-time subjective assessment of interactive multimedia applications , 2014, Multimedia Tools and Applications.

[9]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[10]  Chin-Laung Lei,et al.  Understanding the performance of thin-client gaming , 2011, 2011 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR).

[11]  Ragnhild Eg,et al.  Can gamers detect cloud delay? , 2014, 2014 13th Annual Workshop on Network and Systems Support for Games.

[12]  Jeremy Sugerman,et al.  GPU virtualization on VMware's hosted I/O architecture , 2008, OPSR.

[13]  Lin Shi,et al.  vCUDA: GPU accelerated high performance computing in virtual machines , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[14]  Chao-Tung Yang,et al.  Using PCI Pass-Through for GPU Virtualization with CUDA , 2012, NPC.

[15]  Filip De Turck,et al.  A hybrid thin-client protocol for multimedia streaming and interactive gaming applications , 2006, NOSSDAV '06.

[16]  Wei Cai,et al.  Toward Gaming as a Service , 2014, IEEE Internet Computing.

[17]  Tobias Hoßfeld,et al.  Gaming in the clouds: QoE and the users' perspective , 2013, Math. Comput. Model..

[18]  Gwendal Simon,et al.  A hybrid edge-cloud architecture for reducing on-demand gaming latency , 2014, Multimedia Systems.

[19]  Mark Claypool,et al.  On the performance of OnLive thin client games , 2014, Multimedia Systems.

[20]  Yin Wang,et al.  VGRIS: Virtualized GPU Resource Isolation and Scheduling in Cloud Gaming , 2013, TACO.

[21]  Mohsen Jamali Langroodi,et al.  Complexity Aware Encoding of the Motion Compensation Process of the H.264/AVC Video Coding Standard , 2014, NOSSDAV.

[22]  Xiaohong Jiang,et al.  Analyzing and Modeling the Performance in Xen-Based Virtual Cluster Environment , 2010, 2010 IEEE 12th International Conference on High Performance Computing and Communications (HPCC).

[23]  Brian D. Noble,et al.  The end-to-end performance effects of parallel TCP sockets on a lossy wide-area network , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[24]  Ryan Shea,et al.  Cloud gaming: architecture and performance , 2013, IEEE Network.

[25]  Shervin Shirmohammadi,et al.  Game as video: bit rate reduction through adaptive object encoding , 2013, NOSSDAV '13.

[26]  Hua-Jun Hong,et al.  Placing Virtual Machines to Optimize Cloud Gaming Experience , 2015, IEEE Transactions on Cloud Computing.

[27]  Cheng-Hsin Hsu,et al.  GamingAnywhere: an open cloud gaming system , 2013, MMSys.

[28]  Ryan Shea,et al.  On GPU pass-through performance for cloud gaming: Experiments and analysis , 2013, 2013 12th Annual Workshop on Network and Systems Support for Games (NetGames).

[29]  Saverio Niccolini,et al.  A closer look at thin-client connections: statistical application identification for QoE detection , 2012, IEEE Communications Magazine.

[30]  Jian He,et al.  iCloudAccess: Cost-Effective Streaming of Video Games From the Cloud With Low Latency , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[31]  José Alberto Hernández,et al.  Dissecting the protocol and network traffic of the OnLive cloud gaming platform , 2014, Multimedia Systems.

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