On Rate-Limiting in Mobile Data Networks

With the rapid deployment of LTE/5G services, mobile subscribers now have access to high-speed services approaching Gbps. However, most mobile data plans have data quota from a few GBs up, beyond which the subscriber will be restricted to much lower bandwidth (e.g., 1 Mbps) – rate-limited service. Rate limiting not only poses a significant challenge to service providers, as it is often mistaken for network problems, triggering false alarms at the providers, but may also cause significant performance anomalies at the application layer and transport layer. This work tackles two central problems in mobile network rate-limiting, namely rate-limiting classification and parameter estimation, through a novel model-based online rate-limiter (MODRL) detector that can detect the presence of rate limiting and estimate its parameters passively from transport layer ACK. Experiments in controlled network testbed and production 4G/5G mobile networks show that MODRL can achieve remarkably high and consistent classification accuracy across a wide range of networks. Preliminary results from integrating MODRL into adaptive video streaming and QUIC transport demonstrate that it can effectively eliminate the performance anomalies caused by rate limiting, and open new avenues to further optimize protocol performance over rate-limited mobile networks.