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BOLA360: Near-optimal View and Bitrate Adaptation for 360-degree Video Streaming
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DOI：10.1145/3785137.png)
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Abstract
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Recent advances in omnidirectional cameras and AR/VR headsets have spurred the adoption of 360 degrees videos, which are widely believed to be the future of online video streaming. 360 degrees videos allow users to wear a head-mounted display (HMD) and experience the video as if they are physically present in the scene. Streaming high-quality 360 degrees videos at scale is an unsolved problem that is more challenging than traditional (2D) video delivery. The data rate required to stream 360 degrees videos is an order of magnitude more than traditional videos. Further, the penalty for rebuffering events where the video freezes or displays a blank screen is more severe as it may cause cybersickness. We propose an online adaptive bitrate (ABR) algorithm for 360 degrees videos called BOLA360 that runs inside the client's video player and orchestrates the download of video tiles from the server to maximize the quality-of-experience (QoE) of the user. BOLA360 conserves bandwidth by downloading only those video tiles that are likely to fall within the field-of-view (FOV) of the user. In addition, BOLA360 continually adapts the bitrate of the downloaded video tiles so as to enable a smooth playback without rebuffering. We prove that BOLA360 is near-optimal with respect to an optimal offline algorithm that maximizes QoE. Further, we evaluate BOLA360 on a wide range of network and user head movement profiles and show that it provides 6% to 110% improvements to the QoE of state-of-the-art algorithms. While ABR algorithms for traditional (2D) videos have been well-studied over the last decade, our work is the first ABR algorithm for 360 degrees videos with both theoretical and empirical guarantees on its performance.
Keywords:
Online video streaming
quality of experience
bitrate selection
view adaptation
360-degree video streaming
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