Difference between revisions of "Cloud Gaming"

From NMSL
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* [http://www.cs.sfu.ca/~mhefeeda/ Mohamed Hefeeda]
 
* [http://www.cs.sfu.ca/~mhefeeda/ Mohamed Hefeeda]
  
== Software and  Datasets ==
+
== Code and  Datasets ==
  
 
* [https://github.com/omossad/DeepGame DeepGame: Efficient Video Encoding for Cloud Gaming]
 
* [https://github.com/omossad/DeepGame DeepGame: Efficient Video Encoding for Cloud Gaming]

Revision as of 12:00, 6 August 2021

Cloud gaming is a large, rapidly growing, multi-billion-dollar industry. Cloud gaming enables users to play games on thin clients such as tablets, smartphones, and smart TVs without worrying about processing power, memory size, graphics card capabilities. It allows high-quality games to be played virtually on any device and anywhere, without the need for high-end gaming consoles or installing/updating software. This significantly increases the potential number of users and thus the market size. Most major IT companies offer cloud gaming services, such as Sony PlayStation Now, Google Stadia, Nvidia GeForce Now, and Amazon Tempo.

Cloud gaming essentially moves the game logic and rendering from the user’s device to the cloud. As a result, the entire game runs on the cloud and the rendered scenes are then streamed to users in real-time. Rendering and streaming from the cloud, however, substantially increase the required bandwidth to serve gaming clients. Moreover, given the large-scale and heterogeneity of clients, numerous streams need to be created and served from the cloud in real-time, which creates a major challenge for cloud gaming providers. Thus, minimizing the resources needed to render, encode, customize, and deliver gaming streams to millions of users is an important problem. This problem gets more complex when we consider advanced and next-generation games such as ultra-high definition and immersive games, which are getting popular.

In this project, we partner with AMD Canada with the goal of designing next-generation cloud gaming systems that optimize the quality, bitrate, and delay, which will not only improve the quality of experience for both the players and viewers, but will also reduce the cost and minimize resources for service providers.

People

  • Mohamed Hegazy (MSc student)
  • Ihab Amer (AMD Fellow)

Code and Datasets

Publications

  • M. Hegazy, K. Diab, M. Saeedi, B. Ivanovic, I. Amer, Y. Liu, G. Sines, and M. Hefeeda, Content-aware Video Encoding for Cloud Gaming. In Proc. of ACM Multimedia Systems Conference (MMSys'19), Amherst, MA, June 2019. (received the Best Student Paper Award and the ACM Artifacts Evaluated and Functional badge)