An adaptive distributed call admission control for QoS-sensitive wireless mobile networks
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Bibliographic record
Abstract
This paper introduces an adaptive distributed call admission control framework developed for cellular mobile networks. The main feature of the proposed framework is a more efficient support for mobile multimedia users having dynamic bandwidth requirements. This is achieved by imposing an upper bound on the experienced call dropping probability, regardless of network load changes, while maintaining a high network resource utilization. The call admission control algorithm presented in this paper involves not only the original cell (handling the new admission request) but also a cluster of neighboring cells. The neighboring cells provide significant information about their ability to support the new mobile user in the future. This distributed process allows the original cell to make a more clear-sighted admission decision for the new user. The cell changes the acceptance threshold dynamically to maintain a target call dropping probability. Simulations are provided to show the improvements obtained using our framework.
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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 | 0.001 |
| Open science | 0.002 | 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