Low-Latency VR Video Processing-Transmitting System Based on Edge Computing

The widespread use of live streaming necessitates low-latency requirements for the processing and transmission of virtual reality (VR) videos. This paper introduces a prototype system for low-latency VR video processing and transmission that exploits edge computing to harness the computational power of edge servers. This approach enables efficient video preprocessing and facilitates closer-to-user multicast video distribution. Despite edge computing's potential, managing large-scale access, addressing differentiated channel conditions, and accommodating diverse user viewports pose significant challenges for VR video transcoding and scheduling. To tackle these challenges, our system utilizes dual-edge servers for video transcoding and slicing, thereby markedly improving the viewing experience compared to traditional cloud-based systems. Additionally, we devise a low-complexity greedy algorithm for multi-edge and multi-user VR video offloading distribution, employing the results of bitrate decisions to guide video transcoding inversely. Simulation results reveal that our strategy significantly enhances system utility by 44.77 $\%$ over existing state-of-the-art schemes that do not utilize edge servers while reducing processing time by 58.54 %.