Simulation of lead-time scheduling in PMP FWA networks
Bibliographic record
Abstract
The terrestrial Point-to-Multipoint Fixed Wireless Access (PMP FWA) systems have evolved from their first circuit-switched proprietary implementations in the 1970s into flexible, packet-based solutions available to Competitive Local Exchange Carriers (CLEC) for providing POTS and internet access in WAN and MAN. Examples of such systems can be seen in a number of proprietary technologies, as well as in the commercial implementations of the IEEE 802 standards. The purpose of this thesis is to evaluate the performance of a PMP FWA system in the context of today's packet based IntServ infrastructure. The evaluation takes into account three scheduling algorithms (FIFO, strict priority, and lead-time) in a number of different configurations. This thesis also proposes a set of mechanisms that can be introduced into the IntServ framework to support the lead-time scheduling algorithm.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".