Implementation of an IEEE 802.11 link available bandwidth algorithm to allow crosslayering
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
With the popularity and wide adoption of IEEE 802.11 equipment, wireless networks are being used in an increasing number of applications. Wireless links brings new challenges to communications protocols since link quality is unpredictable. To cope with this problem, many recent research proposals have employed cross-layering design. Often, the MAC layer is assumed to provide link quality metrics. Existing IEEE 802.11 radios and drivers do not provide detailed link quality metrics, which restrained a lot of cross-layering work to simulation environment. In this paper, we propose an algorithm that measures and computes link quality metrics inside IEEE 802.11 MAC so that it provides detailed link quality information to other layers of the protocol stack. Among other things, we implemented an algorithm that provides the available bandwidth to each neighbor node in an ad hoc network. This could be used in a number of scenarios to achieve work in the area of cross-layer design in real test beds. Typically, such work has been constrained to simulation or emulation environments due to the lack of link quality metrics provided by IEEE 802.11 MAC drivers.
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 | 0.000 | 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 | 0.001 |
| 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 it