Multi-Layered Telemetry Assessing Global Performance of LEO Internet Providers
Towards a Global Telemetry System for Evaluating LEO ISP Performance
V.S. Graure (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Tanya Shreedhar – Mentor (TU Delft - Networked Systems)
Nitinder Mohan – Mentor (TU Delft - Networked Systems)
Q. Wang – Graduation committee member (TU Delft - Embedded Systems)
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Abstract
The rise of Low-Earth-Orbit (LEO) satellite networks, such as Starlink, has transformed global connectivity, enabling high-speed internet access in previously underserved regions. However, existing research lacks a unified framework to evaluate and compare the performance of LEO ISPs against terrestrial alternatives using heterogeneous measurement datasets. In this work, we present a methodology for harmonizing and standardizing passive internet measurements from M-Lab’s NDT7 and Cloudflare’s AIM datasets, implemented in the form of the Global Telemetry System. These sources are integrated through schema unification, filtering, and normalization to produce a reproducible and geographically comprehensive telemetry dataset. We introduce a server-based filtering approach to mitigate geographic and routing biases, and we evaluate aggregation methods to align measurement distributions across datasets. Our results demonstrate the dataset integration methodology preserves key distributional properties, enabling fair and statistically consistent merging of measurements from the two sources. This work represents a first step toward a scalable and extensible telemetry infrastructure for assessing next-generation global internet services.