Two-tier On-demand Streaming

We propose an innovative chunk-based streaming framework, featuring two-tier video coding and delivery: the base tier prefetches chunks covering 360-degree view at low quality using a long buffer, while the enhancement tier requests chunks covering the predicted user view window at high quality. We study optimal rate allocation between the two tiers to strike the desired balance between the rendered video quality and streaming robustness to bandwidth and FoV dynamics. We develop chunk-based video rate selection and view-span adaptation algorithms using both model-based feedback control loops and model-free reinforcement learning.

• L. Sun, F. Duanmu, Y. Liu, Y. Wang, Y. Ye, H. Shi, and D. Dai, “A Two-Tier System for On-Demand Streaming of 360 Degree Video Streaming over Dynamic Networks,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2019.
• Liyang Sun, Fanyi Duanmu, Yong Liu, Yao Wang, Yihua Ye, Hang Shi, David Dai, Multi-path Multi-tier 360-degree Video Streaming in 5G Networks, ACM Multimedia System Conference (MMSys), Amsterdam, Netherland, 2018.
• Fanyi Duanmu, Eymen Kurdoglu, Yong Liu, Yao Wang, View Direction and Bandwidth Adaptive 360 Degree Video Streaming Using a Two-Tier System, IEEE International Symposium on Circuits and Systems (ISCAS), 2017.
• Fanyi Duanmu, Eymen Kurdoglu, S. Amir Hosseini, Yong Liu and Yao Wang, Prioritized Buffer Control in Two-tier 360 Video Streaming, ACM SigComm Workshop on VR/AR Network, 2017.