Ebublio: Edge Assisted Multi-user 360-Degree Video Streaming

2022 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2022)(2022)

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摘要
Compared to traditional videos, streaming 360 degrees videos is more difficult. We propose Ebublio, a novel intelligent edge caching framework consisting of a collaborative FoV prediction (CFP) module and a long-term tile caching optimization (LTO) module. The former integrates the features of video content, user trajectory, and other users' records for combined prediction. The latter employs the Lyapunov framework and a subgradient optimization toward the optimal caching replacement policy. Our trace-driven evaluation further demonstrates the superiority of our framework, with about 42% improvement in FoV prediction, and 36% improvement in QoE under similar traffic consumption.
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关键词
Virtual reality, 360 degrees video, 360 degrees video streaming, Virtual reality, 360 degrees video, FoV predication, Networking, Edge computing and caching, Optimization, Lyapunov optimization
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