FBDT: Forward and Backward Data Transmission Across RATs for High Quality Mobile 360-Degree Video VR Streaming

被引:0
|
作者
Srinivasan, Suresh [1 ]
Shippey, Sam [1 ]
Aryafar, Ehsan [1 ]
Chakareski, Jacob [2 ]
机构
[1] Portland State Univ, Portland, OR 97207 USA
[2] New Jersey Inst Technol, Newark, NJ 07102 USA
关键词
Transport Layer Protocol; Rate Distortion; Virtual Reality;
D O I
10.1145/3587819.3590987
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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. lookaround 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.
引用
收藏
页码:130 / 141
页数:12
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