# A Network Analysis on Cloud Gaming: Stadia, GeForce Now and PSNow
## 3 Measurement Collection  
In this section, we describe our experimental testbed and the dataset that we collect. We focus on three cloud gaming services, namely Stadia, GeForce Now, and PS Now, on which we created standard accounts that we use for our experiments. We deploy a testbed using three gaming devices: a PC running Windows with a 4K screen, an Android smartphone, and the dedicated Stadia dongle. All devices are connected to the Internet through a Linux gateway equipped with two 1 Gbit/s Ethernet network interfaces and a 300 Mbit/s WiFi 802.11 ac wireless card. The Windows PC is connected to the gateway on the first Ethernet card, while the Android smartphone and the Stadia dongle are connected via WiFi. The gateway uses the second Ethernet interface as an upstream link to the Internet, provided by a 1 Gbit/s Fiber-To-The-Home subscription located in Turin, Italy. Figure 1 sketches our testbed. Stadia runs via the Chrome browser on the Windows PC and its mobile application on the Android phone (we used version 2.13). Moreover, we perform additional experiments using the dedicated Chromecast Ultra dongle, which allows the user to play and connect it to a screen. GeForce Now runs from a specific application in both cases (version 1.0.9 for PC and 5.27.28247374 for Android), while PS Now only works from the PC application (version 11.0.2 was used). We play the three services making gaming sessions approximately 5-10 min long and capturing all the network traffic that the devices exchange with the Internet. We seek reliable results by playing a broad spectrum of video games on all platforms, from first-person shooters to racing and adventure--e.g., Sniper Elite 4, Destiny, Grid, and Tomb Raider. With this testbed, we perform five different experimental campaigns, summarized in Table 1. Firstly, we run different gaming sessions for each platform using the Windows PC, the smartphone and the dongle (when possible). Secondly, we run different gaming sessions by using the Windows PC, and by manually configuring the applications to stream video with different quality levels. This option is available on Stadia and GeForce Now. Thirdly, only for GeForce Now, do we use the Windows application to use one of the 14 available  
Figure 1: Testbed used for the experimental campaigns. data centres by tuning the server location application setting. Next, we artificially impair the network in terms of bandwidth and latency and packet loss to study the behavior of the applications under different network conditions. To this end, we run the tc-netem tool on the Linux gateway to progressively decrease the available bandwidth from 100 to 5 Mbit/s, impose additional latency from 10 to 300 ms, or 1-10% packet loss. For Stadia and GeForce Now, we replicate all the experiments using both the PC and the smartphone. Moreover, we also perform all experiments with the Stadia dongle. Finally, we take Stadia as a case study to understand the behaviour with different mobiles networks. To this end, we perform different gaming sessions with the PC and emulated on the Linux gateway different mobile networks using ERRANT [24]. ERRANT is a state-of-the-art network emulator which imposes realistic network conditions based on a large-scale measurement campaign under operational mobile networks. ERRANT can reproduce the variability of conditions intrinsically rooted in mobile networks due to different operators, radio access technologies (RATs) (i.e., 3G or 4G), or signal quality (e.g., bad quality due to weak signal). ERRANT comes with 32 network profiles describing the typical network conditions observed in different European operators under 3G and 4G. We also use the ERRANT speedtest training dataset to study the possibility of using Stadia on different conditions under mobile networks. In total, we collect 225 packet traces, summing to 390 GB of data. We share with the research community a sample of these traces from the three services at [5]. Then, we analyze the traffic traces using the Wireshark packet analyzer.