Collaborative Edge Caching and Dynamic Bitrate Adaptation for SHVC-based VR Video Streaming

Due to the bandwidth bottleneck in the current wireless network, simultaneous transmission of large-scale, ultrahigh-quality virtual reality (VR) videos for mobile users remains challenging. In response, we analyze the available technical approaches and propose a tiled scalable high efficiency video coding (SHVC) -based VR video collaborative edge caching scheme. The scheme leverages the efficiency and flexibility of SHVC, which can further reduce the scale of VR video streaming and enhances caching efficiency. We then devise a fast algorithm based on submodular optimization to address the NP-completeness and large-scale inputs of the caching problem. Furthermore, a dynamic bitrate adaptation algorithm is designed based on SHVC. We transform the bitrate adaptation of streaming in the wireless network into solving a graph theory problem to handle the inevitable congestion scenarios. Numerical experimental results demonstrate that the proposed caching scheme exhibits outstanding performance in handling large-scale data and outperforms existing caching schemes in terms of delivery delay. When compared to typical approaches, the proposed bitrate adaptation algorithm also demonstrates superior overall performance across multiple metrics.