@article{ART003259714},
author={Jung Soo Han},
title={Real-Time XR Streaming and Synchronization for Autonomous},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2025},
volume={11},
number={5},
pages={20}
TY - JOUR
AU - Jung Soo Han
TI - Real-Time XR Streaming and Synchronization for Autonomous
JO - Journal of Internet of Things and Convergence
PY - 2025
VL - 11
IS - 5
PB - The Korea Internet of Things Society
SP - 20
EP -
SN - 2466-0078
AB - This paper provides an in-depth analysis of the system requirements and implementation strategies for real-time XR streaming and synchronization technologies in autonomous vehicle environments. As autonomous vehicles evolve into mobile experiential spaces, there is an increasing need for XR systems that can simultaneously achieve ultra-low latency, high-precision synchronization, and adaptive responsiveness. To address this, the study examines major streaming protocols such as WebRTC, MPEG-DASH, QUIC, and SRT, along with IEEE 1588 PTP and TSN-based time synchronization technologies. The feasibility of these approaches is further explored through case studies including NVIDIA CloudXR, Edge AI-based predictive rendering, and Intel TCC. The proposed system is structured as a five-layer architecture consisting of a data collector, streaming server, edge gateway, synchronization engine, and XR renderer, with a detailed explanation of the functional roles and interactions across layers. Key technical challenges—such as bandwidth bottlenecks in high-resolution XR content transmission, data reception delays during high-speed mobility, and visual incoherence caused by frame desynchronization —are identified. To address these issues, the study proposes an integrated design approach combining adaptive streaming, MEC-based distributed processing, and precise synchronization algorithms. In conclusion, real-time XR streaming and synchronization technologies are positioned as essential infrastructures that ensure both the safety and immersive user experience of autonomous vehicles. The study emphasizes that a strategic integration of MEC, edge AI, and standardized protocols is crucial for achieving reliable and high-performance XR environments in future autonomous mobility systems.
KW - Autonomous Vehicle;XR Streaming;Edge Computing;Time Synchronization;Ultra-Low;Latency Communication
DO -
UR -
ER -
Jung Soo Han. (2025). Real-Time XR Streaming and Synchronization for Autonomous. Journal of Internet of Things and Convergence, 11(5), 20.
Jung Soo Han. 2025, "Real-Time XR Streaming and Synchronization for Autonomous", Journal of Internet of Things and Convergence, vol.11, no.5 20.
Jung Soo Han "Real-Time XR Streaming and Synchronization for Autonomous" Journal of Internet of Things and Convergence 11.5 20 (2025) : 20.
Jung Soo Han. Real-Time XR Streaming and Synchronization for Autonomous. 2025; 11(5), 20.
Jung Soo Han. "Real-Time XR Streaming and Synchronization for Autonomous" Journal of Internet of Things and Convergence 11, no.5 (2025) : 20.
Jung Soo Han. Real-Time XR Streaming and Synchronization for Autonomous. Journal of Internet of Things and Convergence, 11(5), 20.
Jung Soo Han. Real-Time XR Streaming and Synchronization for Autonomous. Journal of Internet of Things and Convergence. 2025; 11(5) 20.
Jung Soo Han. Real-Time XR Streaming and Synchronization for Autonomous. 2025; 11(5), 20.
Jung Soo Han. "Real-Time XR Streaming and Synchronization for Autonomous" Journal of Internet of Things and Convergence 11, no.5 (2025) : 20.
