Network Optimizations for 360-degree Video Streaming

Published in UCSC and THU, 2017

360-degree video stream has the problems of unnecessary data transmission and high quality QoE requirement in the AR/VR network field. The project aims to predict immersive video user behavior information and select appropriate video content based on network delay estimation as well as adjusting video bit rate.


Key points

  • Combining the network delay, we adjust the bit rate and the user’s field of view adaptively;
  • A user behavior simulation tool based on Markov model and Beta distribution is implemented;
  • A hierachical cache system design for prefetch tiles in high-performace storage and cache the videos in cost-effective storage.