Bottleneck-first scheduling for real-time traffic in IEEE 802.11 infrastructure-based mesh networks
Bibliographic record
Abstract
This paper studies the real-time traffic scheduling in IEEE 802.11 infrastructure-based wireless mesh networks. Providing strict latency guarantee for real-time traffic in a wireless mesh 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 we propose a bottleneck-first scheduling scheme (BFS) for voice traffic. In the proposed scheme, a central station is responsible for making scheduling decisions for all the real-time packet transmissions at the APs. 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 end-to-end hops are scheduled first. Numerical results show that the proposed scheduling scheme achieves low transmission delay and high capacity in the mesh networks, compared to the simple first-come-first-serve scheduling scheme.
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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 | 0.001 | 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 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".