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BOLA360: Near-optimal View and Bitrate Adaptation for 360-degree Video Streaming

Ali Zeynali, Mahsa Sahebdel, Mohammad Hajiesmaili, Ramesh K. Sitaraman

TL;DR

This work proposes an online adaptive bitrate (ABR) algorithm for 360° 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.

Abstract

Recent advances in omnidirectional cameras and AR/VR headsets have spurred the adoption of 360-degree videos that are widely believed to be the future of online video streaming. 360-degree 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-degree videos at scale is an unsolved problem that is more challenging than traditional (2D) video delivery. The data rate required to stream 360-degree 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-degree videos called BOLA360 that runs inside the client's video player and orchestrates the download of video segments from the server so as to maximize the quality-of-experience (QoE) of the user. BOLA360 conserves bandwidth by downloading only those video segments 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 segments 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 $13.6\%$ to $372.5\%$ more QoE than 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-degree videos with both theoretical and empirical guarantees on its performance.

BOLA360: Near-optimal View and Bitrate Adaptation for 360-degree Video Streaming

TL;DR

This work proposes an online adaptive bitrate (ABR) algorithm for 360° 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.

Abstract

Recent advances in omnidirectional cameras and AR/VR headsets have spurred the adoption of 360-degree videos that are widely believed to be the future of online video streaming. 360-degree 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-degree videos at scale is an unsolved problem that is more challenging than traditional (2D) video delivery. The data rate required to stream 360-degree 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-degree videos called BOLA360 that runs inside the client's video player and orchestrates the download of video segments from the server so as to maximize the quality-of-experience (QoE) of the user. BOLA360 conserves bandwidth by downloading only those video segments 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 segments 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 to more QoE than 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-degree videos with both theoretical and empirical guarantees on its performance.
Paper Structure (20 sections, 4 theorems, 19 equations, 17 figures, 5 tables, 2 algorithms)

This paper contains 20 sections, 4 theorems, 19 equations, 17 figures, 5 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. System Model and Problem Formulation
  4. Problem Formulation.
  5. An Optimal Offline Algorithm
  6. BOLA360: An Online 360° ABR Algorithm
  7. Design and Analysis of BOLA360
  8. Theoretical Analysis of BOLA360
  9. Understanding the Behavior of BOLA360
  10. Comparison Algorithms
  11. Experimental Setup
  12. Performance Evaluation using Real Network and Head Movement Traces
  13. Impact of Network Bandwidth
  14. Impact of Head Position Probabilities
  15. Discussion on the Performance of Predictions-based Baseline Algorithms
  16. ...and 5 more sections

Key Result

Theorem 4.1

Algorithm alg:opt_off gives an upper bound for QoE of optimal offline solution for ABR360.

Figures (17)

  • Figure 1: (a) Users watch 360° videos by moving their viewport to point to any direction in the enclosing sphere (b) each frame of the 360° video is broken up into tile frames ZinkSN19.
  • Figure 2: One shot from the entire spatial area of 360° video and FOV of user in that
  • Figure 3: The selected bitrate of BOLA360 for tiles with highest and lowest probability and average selected bitrate as a function of buffer level for homogeneous (left) and heterogeneous (right) distributions.
  • Figure 4: Buffer level variation over time under bitrate selection of BOLA360 for homogeneous (left) and heterogeneous (right) distributions.
  • Figure 5: Variation of average downloaded bitrates over time under bitrate selection of BOLA360 for the homogeneous (left), and heterogeneous (right) head position probability distribution.
  • ...and 12 more figures

Theorems & Definitions (6)

  • Remark 1
  • Theorem 4.1
  • Theorem 5.1
  • Lemma 1
  • Theorem 5.2: main theorem
  • Remark 2: On the conflict between the playback delay and QoE of streaming