QoS-Aware Radio-and-Fiber (R&F) Access-Metro Networks
Bibliographic record
Abstract
Future bimodal fiber-wireless (FiWi) access-metro networks may deploy both radio-over-fiber (RoF) and radio-and-fiber (R&F) technologies. RoF networks are rapidly becoming mature, but they fall short of interworking with distributed wireless MAC protocols such as DCF in widely deployed IEEE 802.11 WLANs. While R&F networks are able to avoid this limitation by means of protocol translation at the optical-wireless interface, recent testbed activities demonstrated that their multimedia QoS performance is far from acceptable, giving rise to various open R&F networking issues. In this paper, we report on our ongoing research activities on providing improved QoS support in R&F access-metro networks by means of (i) hierarchical scheduling and hybrid access control in integrated RPR/WiMAX metro networks, and (ii) hierarchical frame aggregation in integrated EPON/next-generation WLAN-based mesh access 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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".