FBDT:高质量移动360度VR视频流的正向和反向数据传输

S. Srinivasan, Samuel Shippey, Ehsan Aryafar, Jacob Chakareski
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引用次数: 0

摘要

虚拟世界包含许多虚拟世界,并依赖于流媒体高质量的360°视频到VR/AR耳机。这种类型的视频传输需要非常高的数据速率来满足所有客户所需的体验质量(QoE)。通过多种无线接入技术(rat)(如WiFi和WiGig)同时传输数据是满足这种需求的关键解决方案。然而,现有的传输层多rat流量聚合方案存在行首阻塞(Head-of-Line, HoL)和跨rat的次优流量分割问题,特别是当它们的信道条件波动较大时。因此,最先进的多路径TCP (MPTCP)解决方案可以在许多实际环境中实现比仅使用单个WiFi RAT更低的聚合传输数据速率,例如,当客户端是移动的。我们在使用多个rat实现高质量移动360°视频VR流媒体方面做出了两个关键贡献。首先,我们提出了FBDT的设计,这是一种新颖的多路径传输层解决方案,可以实现跨rat的单个传输速率之和,尽管它们的系统动态。我们在Linux内核中实现了FBDT,与最先进的方案相比,传输吞吐量有了实质性的改善,例如,当VR客户端是移动的时候,在双rat场景(WiFi和WiGig)中获得了2.5倍的增益。其次,考虑到客户端如何探索360°环视全景和每个RAT的传输数据速率的统计模型,我们制定了一个优化问题,以最大限度地提高移动VR客户端的视口质量。我们探索了一种迭代方法来解决这个问题,并通过利用我们的测试平台进行测量驱动的模拟来评估其性能。当使用我们的优化框架时,我们发现视口质量增加了12 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FBDT: Forward and Backward Data Transmission Across RATs for High Quality Mobile 360-Degree Video VR Streaming
The metaverse encompasses many virtual universes and relies on streaming high-quality 360° videos to VR/AR headsets. This type of video transmission requires very high data rates to meet the desired Quality of Experience (QoE) for all clients. Simultaneous data transmission across multiple Radio Access Technologies (RATs) such as WiFi and WiGig is a key solution to meet this required capacity demand. However, existing transport layer multi-RAT traffic aggregation schemes suffer from Head-of-Line (HoL) blocking and sub-optimal traffic splitting across the RATs, particularly when there is a high fluctuation in their channel conditions. As a result, state-of-the-art multi-path TCP (MPTCP) solutions can achieve aggregate transmission data rates that are lower than that of using only a single WiFi RAT in many practical settings, e.g., when the client is mobile. We make two key contributions to enable high quality mobile 360° video VR streaming using multiple RATs. First, we propose the design of FBDT, a novel multi-path transport layer solution that can achieve the sum of individual transmission rates across the RATs despite their system dynamics. We implemented FBDT in the Linux kernel and showed substantial improvement in transmission throughput relative to state-of-the-art schemes, e.g, 2.5x gain in a dual-RAT scenario (WiFi and WiGig) when the VR client is mobile. Second, we formulate an optimization problem to maximize a mobile VR client's viewport quality by taking into account statistical models of how clients explore the 360° look-around panorama and the transmission data rate of each RAT. We explore an iterative method to solve this problem and evaluate its performance through measurement-driven simulations leveraging our testbed. We show up to 12 dB increase in viewport quality when our optimization framework is employed.
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