BISCAY
Practical Radio KPI Driven Congestion Control for Mobile Networks
Jon Larrea (Revelare Networks)
Tanya Shreedhar (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Atte Niemi (The University of Edinburgh)
Adel Sefiane (Imperial College London, NVIDIA)
Mahesh K. Marina (The University of Edinburgh)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Mobile application performance is often bottlenecked by cellular links with rapid bandwidth fluctuations. We show that radio KPIs from the device chipset can precisely and promptly measure available cellular bandwidth. Building on this, we propose Biscay, a practical KPI-driven congestion control for mobile networks. Biscay leverages OpenDiag, an in-kernel, real-time KPI extractor we introduce along with a KPI-based bandwidth estimator to adjust the congestion window, utilizing available bandwidth while minimizing delay. We implement Biscay and OpenDiag on unrooted Android 5G phones. Across trace-driven emulations and real-world 4G/5G experiments, Biscay outperforms state-of-the-art CCAs (e.g., BBR, CUBIC), typically reducing average and tail delay by >90% while matching or improving throughput. These gains stem from OpenDiag’s 100× finer on-device KPI granularity than existing alternatives like MobileInsight.
help_outline