Games Are Not Equal: Classifying Cloud Gaming Contexts for Effective User Experience Measurement
To tap into the growing market of cloud gaming, whereby game graphics is rendered in the cloud and streamed back to the user as a video feed, network operators are creating monetizable assurance services that dynamically provision network resources. However, without accurately measuring cloud gaming user experience, they cannot assess the effectiveness of their provisioning methods. Basic measures such as bandwidth and frame rate by themselves do not suffice, and can only be interpreted in the context of the game played and the player activity within the game. This paper equips the network operator with a method to obtain a real-time measure of cloud gaming experience by analyzing network traffic, including contextual factors such as the game title and player activity stage. Our method is able to classify the game title within the first five seconds of game launch, and continuously assess the player activity stage as being active, passive, or idle. We deploy it in an ISP hosting NVIDIA cloud gaming servers for the region. We provide insights from hundreds of thousands of cloud game streaming sessions over a three-month period into the dependence of bandwidth consumption and experience level on the gameplay contexts.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
E-Render: Enabling UHD-Quality Cloud Gaming Through Edge Rendering
Cloud gaming services enable users to enjoy various high-quality computer games without installing them in their devices which may have poor resources. However, it consumes high bandwidth in backbone networks as game v…
Measuring and Estimating Key Quality Indicators in Cloud Gaming services
User equipment is one of the main bottlenecks facing the gaming industry nowadays. The extremely realistic games which are currently available trigger high computational requirements of the user devices to run games. As …
Virtual Reality Gaming on the Cloud: A Reality Check
Cloud virtual reality (VR) gaming traffic characteristics such as frame size, inter-arrival time, and latency need to be carefully studied as a first step toward scalable VR cloud service provisioning. To this end, in th…
ManagementTowards Deep Learning Methods for Quality Assessment of Computer-Generated Imagery
Video gaming streaming services are growing rapidly due to new services such as passive video streaming, e.g. Twitch.tv, and cloud gaming, e.g. Nvidia Geforce Now. In contrast to traditional video content, gaming content…
Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos
We present the outcomes of a recent large-scale subjective study of Mobile Cloud Gaming Video Quality Assessment (MCG-VQA) on a diverse set of gaming videos. Rapid advancements in cloud services, faster video encoding te…
Video Quality AssessmentVisual Question Answering (VQA)