Explora-VR: Content Prefetching for Tile-Based Immersive Video Streaming Applications

Abstract

Despite the growing popularity of immersive video applications during the last few years, the stringent low latency requirements of this kind of services remain a major challenge for the existing network infrastructure. Edge-assisted solutions compensate for network latency by relying on cache-enabled edge servers to bring frequently accessed video content closer to the client. However, these approaches often require historical request traces from previous watching sessions or adopt passive caching strategies subject to the cold-start problem and prone to playout freezes. This paper introduces Explora-VR , a novel edge-assisted content prefetching method for tile-based 360 video streaming. This method leverages the client’s rate adaptation heuristic to preemptively retrieve the content that the viewer will most likely watch in the upcoming segments, and loads it into a nearby edge server. At the same time, Explora-VR incrementally builds a dynamic collective buffer for serving the requests from active streaming sessions based on the estimated popularity of video tiles per segment. An evaluation of the proposed method was conducted on head movement traces collected from 48 unique users while watching three different 360 videos. Results show that Explora-VR is able to serve over 98% of the client requests from the cache-enabled edge server, leading to an average increase of 2.5 and 1.4 in the client’s perceived throughput, compared to a conventional client-server setup and a least recently used caching policy, respectively. This enables Explora-VR to serve higher quality video content while providing a freeze-free playback experience and effectively reducing network traffic to the content server.