Design and Analysis of MEC- and Proactive Caching-Based $360^{\circ }$ Mobile VR Video Streaming

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Abstract
Recently, 360-degree mobile virtual reality video (MVRV) has become increasingly popular because it can provide users with an immersive experience. However, MVRV is usually recorded in a high resolution and is sensitive to latency, which indicates that broadband, ultra-reliable, and low-latency communication is necessary to guarantee the users’ quality of experience. In this paper, we propose a mobile edge computing (MEC)-based 360-degree MVRV streaming scheme with field-of-view (FoV) prediction, which jointly considers video coding, proactive caching, computation offloading, and data transmission. To meet the requirement of stringent end-to-end (E2E) latency, the user’s viewpoint prediction is utilized to cache video data proactively, and computing tasks are partially offloaded to the MEC server. In addition, we propose an analytical model based on diffusion process to study the packet transmission process of 360-degree MVRV in multihop wired/wireless networks and analyze the performance of the MEC-enabled scheme. The simulation results verify the accuracy of the analysis and the effectiveness of the proposed MVRV streaming scheme in reducing the E2E delay. Furthermore, the analytical framework sheds some light on the impacts of system parameters, e.g., FoV prediction accuracy and transmission rate, on the balance between computation delay and communication delay.
Funding Information
  • National Key Research and Development Program of China (2018YFB1801104)
  • National Natural Science Foundation of China (61771427)
  • Zhejiang Provincial Key Project of Research and Development (2021C01119)
  • SUTD-ZJU IDEA (ZJUVP1800104)
  • SUTD Growth Plan Grant for AI
  • Huawei Technologies Company Ltd. (YBN2018115223)