Real-time voice traffic scheduling and its optimization in IEEE 802.11 infrastructure-based wireless mesh networks
Bibliographic record
Abstract
This paper studies real-time voice traffic scheduling in IEEE 802.11 infrastructure-based wireless mesh networks. Providing strict latency guarantee for real-time traffic in such network is difficult, and one of the main challenges is the difficulty in coordinating temporal operations of the mesh access points (APs). In this paper scheduling problem for constant-rate voice traffic is formulated as a binary linear programming problem and its optimal solution is given. The computational complexity may prevent the optimum scheduling from implementing in practice. Then a bottleneck-first scheduling scheme is proposed where scheduling decisions at the APs with a higher traffic load are done before those with a lower traffic load. At each AP, voice packets with more hops to their destinations are scheduled first. Numerical results show that the proposed scheduling scheme can achieve the same network capacity as the optimal one while keeping reasonably low transmission delay.
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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 | 0.001 |
| 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".