Tile-based Multi-source Adaptive Streaming for 360-degree Ultra-High-Definition Videos

360° UHD videos have absorbed great attention in recent years. However, as they are of significant size and usually watched from a close range, they require extremely high bandwidth for a good immersive experience, which poses a great challenge on the current single-source adaptive streaming strategies. Realizing the great potentials of tile-based video streaming and pervasive edge services, we advocate a tile-based multi-source adaptive streaming strategy for 360° UHD videos over edge networks. In order to reap its benefits, we consider a comprehensive model which captures the key components of tile-based multi-source adaptive streaming. Then we formulate a joint bitrate selection and request scheduling problem, aiming at maximizing the system utility (i.e., user QoE minus service overhead) while satisfying the service integrity and latency constraints. To solve the formulated non-linear integer programming problem efficiently, we decouple the control variables and resort to matroid theory to design an optimal master-slave algorithm. In addition, we improve our proposed algorithm with a deep learning-based bitrate selection algorithm, which can achieve a rationalization result in a short running time. Extensive datadriven simulations validate the superior performance of our proposed algorithm.

I. Introduction

Background. 360° or panoramic videos are becoming popular on many video platforms such as YouTube and Facebook, which have attracted great attention from both academic and industry. In general, 360° videos are streamed in a similar way as regular 2D videos (e.g., DASH–Dynamic Adaptive Streaming over HTTP). However, since they are usually watched from a close range via head mounted display and their spherical images contain more pixels, they require much higher bandwidth to achieve a good immersive experience [1]. Such a stringent bandwidth requirement together with the inevitable bandwidth fluctuation poses a great challenge on the current adaptive streaming strategies such as requesting many video segments with low bitrates to alleviate video rebuffering [2], which motivates researchers to pursue novel streaming and advanced network transmission techniques.