Queue Management Strategies to Improve TCP Fairness in IEEE 802.11 Wireless LANs
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Bibliographic record
Abstract
Wireless Local Area Networks (WLANs) based on the IEEE 802.11 technology have become increasingly popular and ubiquitous. The 802.11 standard allows each station in a WLAN equal opportunity to access the wireless channel, which can result in unfair sharing of network bandwidth between upstream and downstream TCP flows at an AP. In this paper, we propose two different queue management techniques to alleviate the unfairness problem, with one based on Selective Packet Marking (SPM), and the other based on Least Attained Service (LAS) scheduling. We evaluate these proposed solutions using the ns-2 network simulator. The simulation results show that, compared to a conventional DropTail queue mechanism for NewReno TCP sources, the proposed solutions improve the fairness index by 20-40%, while achieving comparable aggregate throughput.
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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 | 0.000 | 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 it