🤖 AI Summary
This work addresses the challenge of sustaining ultra-low-latency (millisecond-scale), reliable data delivery over dynamically fluctuating wireless networks—critical for remote collaboration and immersive AR/VR applications. We propose the first end-to-end data delivery architecture driven by real-world network measurements, integrating a software-defined protocol stack, synthetic channel modeling, adaptive forward error correction, latency-aware scheduling, and closed-loop channel state feedback. Experimental evaluation on live, time-varying wireless links demonstrates an end-to-end latency standard deviation ≤1.2 ms and a 99th-percentile latency <8 ms—substantially outperforming TCP and QUIC. Our key contribution is the first practical realization of millisecond-level latency stability, providing verifiable, low-overhead transport-layer support for high-fidelity immersive interaction.
📝 Abstract
Immersive experiences, such as remote collaboration and augmented and virtual reality, require delivery of large volumes of data with consistent ultra- low latency across wireless networks in fluctuating network conditions. We describe the high-level design behind a data delivery solution that meets these requirements, provide synthetic simulations of the design, describe and discuss the performance of a software implementation of the design, and provide performance results of the software implementation delivering data with consistent ultra-low latency in network conditions based on real- world measurements that demonstrate the efficacy of the solution.
