Starlink has deployed over 7,800 satellites serving millions of subscribers, yet predicting its performance remains an open challenge. Rapid orbital dynamics, frequent handovers, and weather-induced signal attenuation create variability that existing models, built on a handful of instrumented terminals in limited regions, cannot capture at global scale. We present Horizon, the first global-scale machine learning system for predicting LEO satellite Internet performance. Our key insight is that crowdsourced measurement platforms, while noisier than controlled experiments, provide the geographic diversity necessary to build globally generalizable models. Horizon integrates 11 months of measurements from M-Lab and Cloudflare spanning 90+ countries with meteorological data and satellite orbital propagation features. On a fully held-out one-week temporal window, Horizon achieves mean absolute errors of 17.76 ms for latency and 25.63 Mbps for throughput; on a standard 80/20 split it outperforms all baselines, including adaptations of state-of-the-art architectures. Feature importance analysis reveals that geographic position dominates prediction, with latitude alone contributing 42-46%, while weather features account for 14-15%, quantifying the impact of atmospheric conditions on Ku/Ka-band links. Leave-one-location-out experiments confirm that Horizon generalizes to regions absent from training, enabling performance estimation where measurement infrastructure does not yet exist. Our dataset and pipeline are publicly available, providing a foundation for global LEO network performance visibility.

Multipath TCP (MPTCP) extends traditional TCP to enable simultaneous use of multiple connection endpoints at the source and destination. MPTCP has been under active development since its standardization in 2013, and more recently in February 2020, MPTCP was upstreamed to the Linux kernel. In this paper, we provide the first broad analysis of MPTCPv0 in the Internet. We probe the entire IPv4 address space and an IPv6 hitlist to detect MPTCP-enabled systems operational on port 80 and 443. Our scans reveal a steady increase in MPTCP-capable IPs, reaching 9k+ on IPv4 and a few dozen on IPv6. We also discover a significant share of seemingly MPTCP-capable hosts, an artifact of middleboxes mirroring TCP options. We conduct targeted HTTP(S) measurements towards select hosts and find that middleboxes can aggressively impact the perceived quality of applications utilizing MPTCP. Finally, we analyze two complementary traffic traces from CAIDA and MAWI to shed light on the real-world usage of MPTCP. We find that while MPTCP usage has increased by a factor of 20 over the past few years, its traffic share is still quite low.