Di Domenico, Andrea and Perna, Gianluca and Trevisan, Martino and Vassio, Luca and Giordano, Danilo (2021) A Network Analysis on Cloud Gaming: Stadia, GeForce Now and PSNow. Network, 1 (3). pp. 247-260. ISSN 2673-8732
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Abstract
Cloud gaming is a class of services that promises to revolutionize the videogame market. It allows the user to play a videogame with essential equipment while using a remote server for the actual execution. The multimedia content is streamed through the network from the server to the user. Hence, this service requires low latency and a large bandwidth to work properly with low response time and high-definition video. Three of the leading tech companies (Google, Sony, and NVIDIA) entered this market with their products, and others, like Microsoft and Amazon, are also launching their platforms. However, these companies have released little information about their cloud gaming operation and how they utilize the network. In this work, we study cloud gaming services from the network point of view. We collect more than 200 packet traces under different application settings and network conditions from a broadband network to poor mobile network conditions, for 3 cloud gaming services, namely Stadia from Google, GeForce Now from NVIDIA and PS Now from Sony. We analyze the employed protocols and the workload that they impose on the network. We find that GeForce Now and Stadia use the RTP protocol to stream the multimedia content, with the latter relying on the standard WebRTC APIs. Depending on the network and video quality, they result in bandwidth-hungry services consuming up to 45 Mbit/s. PS Now instead uses only undocumented protocols and never exceeds 13 Mbit/s. 4G mobile networks can often sustain these loads, while traditional 3G connections struggle. The systems quickly react to deteriorated network conditions, and packet losses up to 5% do not cause a reduction in resolution.
Item Type: | Article |
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Subjects: | STM Academic > Computer Science |
Depositing User: | Unnamed user with email support@stmacademic.com |
Date Deposited: | 13 Jun 2023 07:57 |
Last Modified: | 19 Jan 2024 11:37 |
URI: | http://article.researchpromo.com/id/eprint/1049 |