Structural Unfairness in 802.11-basedWireless Mesh Networks
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
The use of multi-hop wireless networks based on 802.11 technology is extensive and growing, owing to their ease of deployment and low cost. However, such networks exhibit poor fairness, starving nodes that are too many hops distant from the gateway. The best current solution to this problem is source rate limiting. While effective in many topologies, this fails to completely address the fairness problem. In this paper we investigate this problem of residual unfairness in multi-hop wireless networks that use source-rate limiting. We identify the five necessary conditions for its occurrence, showing that elimination of any of these conditions is sufficient to remove the remaining unfairness. For cases where the conditions are unavoidable, we present two simple changes that can ameliorate the problem, providing on average 30% improvement for the least-rate flow.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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