Saturation throughput of IEEE 802.11e EDCA based on mean value analysis
Bibliographic record
Abstract
The IEEE 802.11-based wireless LANs have been widely deployed for local area high-speed data access. The IEEE 802.11e amendment aims at providing QoS provisioning to support real-time multimedia traffic in WLANs. The enhanced distributed channel access (EDCA) is a QoS extension of the distributed coordination function (DCF) in IEEE 802.11a/b/g. In this paper, we propose an analytical model to evaluate the saturation throughput of the IEEE 802.11e EDCA. Our analytical model is based on the use of mean value analysis. We carry out extensive simulation study to validate the accuracy of the proposed model. Our scheme models accurately the effects of the change of contention window size and AIFS (arbitration inter-frame space). Our analytical model is applicable to real-time system tuning and on-line admission control algorithms which require a low computation complexity
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".