Online Bitrate Selection for Viewport Adaptive 360-Degree Video Streaming

TL;DR

This paper introduces OBS360, an online bitrate selection algorithm for viewport adaptive 360-degree video streaming that dynamically adapts to user FoVs and network conditions, significantly improving user QoE.

Contribution

The paper proposes a novel online algorithm, OBS360, with proven sublinear regret, for adaptive bitrate selection in viewport-based 360-degree video streaming without prior user viewing history.

Findings

Improves user QoE by increasing viewing bitrate.

Reduces degradation losses within and between segments.

Outperforms existing methods in simulations.

Abstract

360-degree video streaming provides users with immersive experience by letting users determine their field-of-views (FoVs) in real time. To enhance the users' quality of experience (QoE) given their limited bandwidth, recent works have proposed a viewport adaptive 360-degree video streaming model by exploiting the bitrate adaptation in spatial and temporal domains. Under this video streaming model, in this paper, we consider a scenario with a newly generated 360-degree video without viewing history from other users. To maximize the user's QoE, we propose an online bitrate selection algorithm, called OBS360. The proposed online algorithm can adapt to the unknown and heterogeneous users' FoVs and downloading capacities. We prove that the proposed algorithm achieves sublinear dynamic regret under a convex decision set. This suggests that as the number of video segments increases, the performance of the online algorithm approaches the performance of the offline algorithm, where the users' FoVs and downloading capacities are known. We perform simulations with real-world dataset to evaluate the performance of the proposed algorithm. Results show that compared with several existing methods, our proposed algorithm can enhance the users' QoE significantly by improving the viewing bitrate and reducing the inter-segment and intra-segment degradation losses of the users.