Power-Efficient Live Virtual Reality Streaming Using Edge Offloading
Proceedings of the 32nd Workshop on Network and Operating Systems Support for Digital Audio and Video(2022)
摘要
This paper aims to address the significant power challenges in live virtual reality (VR) streaming (a.k.a., 360-degree video streaming), where the VR view rendering and the advanced deep learning operations (e.g., super-resolution) consume a considerable amount of power draining the battery-constrained VR headset. We develop EdgeVR, a power optimization technique for live VR streaming, which offloads the on-device VR rendering and deep learning operations to an edge server for power savings. To address the significantly increased motion-to-photon (MtoP) latency due to the edge offloading, we develop a live VR viewport prediction method to pre-render the VR views on the edge server and compensate for the round-trip delays. We evaluate the effectiveness of EdgeVR using an end-to-end live VR streaming system with an empirical VR head movement dataset involving 48 users watching 9 VR videos. The results reveal that EdgeVR achieves power-efficient live VR streaming with low MtoP latency.
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关键词
Live streaming,virtual reality,power efficiency
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