Scheduling multiservice traffic for wireless ATM transmission over TDMA/TDD channels
Bibliographic record
Abstract
A centralized dynamic priority based burst level per-VC cell scheduling scheme is proposed for transmission of multiservice traffic over TDMA/TDD channels in a wireless ATM network. In the proposed scheduling scheme the number of slots allocated to a VC (virtual circuit) is changed dynamically depending on the traffic type, traffic load, TOE (time of expiry) value of the data burst and data burst length. The performance of the proposed scheme is evaluated through computer simulation for realistic voice, video and data traffic models and their QoS requirements. Simulation results show that, the proposed scheme can provide reasonably high channel utilization with QoS guarantee in a multiservice traffic environment. Such a scheme is easy to implement and can result in an energy efficient TDMA/TDD MAC (medium access control) protocol for broadband wireless access. In addition, it can be easily adapted as a MAC scheme in the emerging DS (differentiated services) enhanced wireless IP networks.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".