Online Caching Algorithm for VR Video Streaming in Mobile Edge Caching System

The transmission optimization of VR video streaming can improve the quality of user experience, which includes content prediction optimization and caching strategy optimization. Existing work either focuses on content prediction or on caching strategy. However, in the end-edge-cloud system, prediction and caching should be considered together. In this paper, we jointly optimize the four stages of prediction, caching, computing and transmission in mobile edge caching system, aimed to maximize the user's quality of experience. In terms of caching strategy, we design a caching algorithm VIE with unknown future request content, which can efficiently improve the content hit rate, as well as the durations for prediction, computing and transmission. The VIE caching algorithm is proved to be ahead of other algorithms in terms of delay. We optimize the four stages under arbitrary resource allocation and obtain the optimal results. Finally, under the real scenario, the proposed caching algorithm is verified by comparing with several other caching algorithms, simulation results show that the user's QoE is improved under the proposed caching algorithm.