Bibliographic record
Abstract
Low-Earth-Orbit (LEO) satellite constellations are narrowing the performance gap between satellite networks and the terrestrial Internet. Low-latency satellite Internet offered by Starlink enables functionalities that are otherwise unachievable with the traditional geosynchronous equatorial orbit (GEO) satellite networks, including low-latency live video streaming, cloud gaming and real-time video conferencing. The absence of a comprehensive and long-term network measurement dataset with a global perspective poses significant challenges for researchers to evaluate the application performance over Starlink networks. In this paper, we introduce LENS, which is a LEO satellite network measurement dataset, collected from 13 Starlink dishes, associated with 7 Point-of-Presence (PoP) locations across 3 continents. The dataset currently consists of network latency traces from Starlink dishes with different hardware revisions, various service subscriptions and distinct sky obstruction ratios. We provide a high-level overview and analysis of the latency performance using the dataset and discuss various use cases. This dataset is useful for researchers who wish to understand the long-term network performance of Starlink and to evaluate and optimize the performance of multimedia applications over satellite networks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.057 | 0.025 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".