A slot assignment protocol for indoor wireless ATM networks using the channel characteristics and the traffic parameters
Bibliographic record
Abstract
The rapid development of wireless in-building communication systems, has widened the scope of supported applications. Remote terminals may be capable of producing broadband real-time traffic such as variable bit-rate (VBR) video or highly bursty instantaneous file transfers. So one of the important issues in indoor broadband wireless networks (IBWN) is employment of an efficient bandwidth management protocol. In such a protocol, both the effects of radio channel behavior and the traffic heterogeneity have to be considered. In this paper we present a bandwidth allocation scheme based on the interplay of the radio channel characteristics and the traffic statistical parameters and requirements. In this scheme the base station visits the terminals in a non-uniform cyclic fashion. The intervisit interval and the amount of service which is provided to a user during each visit, is determined based on the channel and traffic parameters. This system is evaluated by simulations and is found to provide improved performance in handling the requirements of multimedia services in IBWN.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".