TY - GEN
T1 - FBDT
T2 - 14th ACM Multimedia Systems Conference, MMSys 2023
AU - Srinivasan, Suresh
AU - Shippey, Sam
AU - Aryafar, Ehsan
AU - Chakareski, Jacob
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/6/7
Y1 - 2023/6/7
N2 - 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.
AB - 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.
KW - rate distortion
KW - transport layer protocol
KW - virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85163578874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85163578874&partnerID=8YFLogxK
U2 - 10.1145/3587819.3590987
DO - 10.1145/3587819.3590987
M3 - Conference contribution
AN - SCOPUS:85163578874
T3 - MMSys 2023 - Proceedings of the 14th ACM Multimedia Systems Conference
SP - 130
EP - 141
BT - MMSys 2023 - Proceedings of the 14th ACM Multimedia Systems Conference
PB - Association for Computing Machinery, Inc
Y2 - 7 June 2023 through 10 June 2023
ER -