Quality of Service Impact on Edge Physics Simulations for VR
Sebastian Friston, Elias Griffith, David Swapp, Caleb Lrondi, Fred P. Jjunju, Ryan Ward, Alan Marshall, Anthony Steed
摘要
Mobile HMDs must sacrifice compute performance to achieve ergonomic and power requirements for extended use. Consequently, applications must either reduce rendering and simulation complexity - along with the richness of the experience - or offload complexity to a server. Within the context of edge-computing, a popular way to do this is through render streaming. Render streaming has been demonstrated for desktops and consoles. It has also been explored for HMDs. However, the latency requirements of head tracking make this application much more challenging. While mobile GPUs are not yet as capable as their desktop counterparts, we note that they are becoming more powerful and efficient. With the hard requirements of VR, it is worth continuing to investigate what schemes could optimally balance load, latency and quality. We propose an alternative we call edge-physics: streaming at the scene-graph level from a simulation running on edge-resources, analogous to cluster rendering. Scene streaming is not only straightforward, but compute and bandwidth efficient. The most demanding loops run locally. Jobs that hit the power-wall of mobile CPUs are off-loaded, while improving GPUs are leveraged, maximising compute utilisation. In this paper we create a prototypical implementation and evaluate its potential in terms of fidelity, bandwidth and performance. We show that an effective system which maintains high consistencies on typical edge-links can be easily built, but that some traditional concepts are not applicable, and a better understanding of the perception of motion is required to evaluate such a system comprehensively.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
相关 Paper
- Edge-assisted Real-time Dynamic 3D Point Cloud Rendering for Multi-party Mobile Virtual RealityXiming Wu, Kongyange Zhao, Xu Chen, Teng LiangACM MM 2024 · 被引用 2 次
- Instant Reality: Gaze-Contingent Perceptual Optimization for 3D Virtual Reality StreamingShaoyu Chen, Budmonde Duinkharjav, Xin Sun, Li-Yi Wei 等IEEE VR 2022 · 被引用 25 次
- CollabVr: Reprojection-Based Edge-Client Collaborative Rendering for Real-Time High-Quality Mobile Virtual RealityZhihui Ke, Xiaobo Zhou, Dadong Jiang, Hao Yan 等RTSS 2023 · 被引用 6 次
- Q-VR: system-level design for future mobile collaborative virtual realityChenhao Xie, Xie Li, Yang Hu, Huwan Peng 等ASPLOS 2021 · 被引用 36 次
- EdgeGaussian: Real-time Free-Viewpoint Video for Mobile VR via Edge-Client Collaborative Neural RenderingZhihui Ke, Xiaobo Zhou, Yuyang Liu, Zhizhuo Pang 等MobiCom 2025 · 被引用 1 次
