WSN17-5: A Novel Admission Control for Asynchronous Active Link Protected Ad Hoc Networks
Bibliographic record
Abstract
In this paper we introduce a novel admission control scheme adapted to asynchronous power control for ad hoc networks. An admission control algorithm helps a new link to decide whether it can achieve its required QoS while the network is stable. Most admission control algorithms are categorized either as time-out or SIR-saturation based algorithms. Both of these algorithms are based on QoS convergence of the new link and require some design parameters for each network configuration. Sometimes if an originally admissible link has a low SIR convergence it will be considered as an inadmissible one and forced to drop out. The proposed algorithm in this paper is designed based on the local measurements of the new link in an asynchronous power control with active link protection ad hoc network. In a network of N links, it can determine definite admissibility of the new link in N power update iterations. This algorithm is much faster than time-out and SIR-saturation based schemes and also does not need any design parameters to be updated. Although this algorithm is adapted to a specific power control algorithm, it can be extended to more general cases.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".