A distributed fluid dynamic motivated quality assurance algorithm for multi-hop wireless transmissions
Bibliographic record
Abstract
Wireless networks have becomes one of the most important networks in peoples' lives, due to the convenience and the widespread use of wireless devices. One of the main problems of wireless networks is the unstable network performance, which is a critical issue for multimedia traffic. Stable network performance is critical for the achieving of Quality of Service (QoS) assurance on wireless networks. Even though some techniques are proposed to solve this problem, like Enhanced Distributed Channel Access (EDCA) and Hybrid Coordination Function Channel Access (HCCA), documented in IEEE802.11e, these techniques ignore the multi-hop flow control essential for QoS assurance. The control of the contention window range on the source node is not sufficient to guarantee the throughput, while the traffic flow shares a path with other traffic. The author proposes a fluid dynamic based distributed multi-hop QoS assurance algorithm based on the transmission rate and the contention window range. Based on the analysis, the author designed a distributed system, which only controls a one hop neighbor to handle the QoS requirements. Several simulations were conducted to verify this research, and the simulation results proved that the proposed algorithm is able to provide QoS assurance for multi-hop transmissions.
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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 | 0.001 |
| 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".