不同网络条件下云游戏服务适配分析及QoE评价——以NVIDIA GeForce NOW为例

M. Sužnjević, Iva Slivar, Lea Skorin-Kapov
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引用次数: 26

摘要

云游戏代表了一种高度互动的服务,游戏逻辑在云中呈现,并作为视频流传输到终端设备。虽然它的优点是能够将高质量的图像游戏传输到几乎任何终端用户设备上,但缺点是带宽要求高,延迟很低。因此,云游戏服务提供商面临的一个挑战是设计适应视频流参数的算法,以满足最终用户系统和网络资源的限制。本文针对不同的网络条件,分析了商用NVIDIA GeForce NOW游戏流媒体平台的自适应机制。我们进一步进行了一项涉及GeForce NOW平台的经验用户研究,以评估采用这种适应机制时玩家的体验质量。研究结果揭示了目前部署的机制的局限性,并旨在为设计未来视频编码适应策略的建议提供输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and QoE evaluation of cloud gaming service adaptation under different network conditions: The case of NVIDIA GeForce NOW
Cloud gaming represents a highly interactive service whereby game logic is rendered in the cloud and streamed as a video to end devices. While benefits include the ability to stream high-quality graphics games to practically any end user device, drawbacks include high bandwidth requirements and very low latency. Consequently, a challenge faced by cloud gaming service providers is the design of algorithms for adapting video streaming parameters to meet the end user system and network resource constraints. In this paper, we conduct an analysis of the commercial NVIDIA GeForce NOW game streaming platform adaptation mechanisms in light of variable network conditions. We further conduct an empirical user study involving the GeForce NOW platform to assess player Quality of Experience when such adaptation mechanisms are employed. The results provide insight into limitations of the currently deployed mechanisms, as well as aim to provide input for the proposal of designing future video encoding adaptation strategies.
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