Efficient policing for screen mirroring traffic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The greediness of multimedia applications in terms of their bandwidth demands calls for new and efficient network traffic control mechanisms, especially in wireless networks where the bandwidth is limited. In an enterprise-like environment, an additional burden is expected to be added to the network by screen mirroring traffic. Smart mobile devices are displacing personal computers in many daily applications but at the same time users still need to use a large display, keyboard and mouse. Hence, the transmission of low-latency, high fidelity video over a Wi-Fi link can lead to significant unfairness among users in terms of the bandwidth that is available to them, if this wireless video traffic is not accurately policed. In this work, we focus on the problem of policing screen mirroring traffic. We evaluate various classic and new traffic policing mechanisms, and we propose a new mechanism which is shown to clearly outperform all other mechanisms, including the widely used token bucket policer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it