MoVIE: A Measurement Tool for Mobile Video Streaming on Smartphones
Bibliographic record
Abstract
Mobile video streaming is becoming increasingly popular. In this paper, we describe the design and implementation of a cross-platform measurement tool called MoVIE (Mobile Video Information Extraction) for video streaming on mobile devices. MoVIE is a client-side traffic analyzer that studies smartphone video streaming from different viewpoints. It collects information about network-level packet traffic, transport-layer flows, and application-level video player activities. Then it identifies relationships within the collected data to make mobile video streaming activities transparent. MoVIE is an open-source tool with a graphical user interface. In addition to network traffic measurement, MoVIE supports objective Quality of Experience (QoE) evaluation of video streaming. These features make MoVIE a powerful tool for network traffic measurement, multimedia streaming studies, and privacy analysis. We illustrate MoVIE' scapabilities with a small case study of streaming 360° videos.
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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) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".