Reliable and fast restoration for a survivable wireless-optical broadband access network
Bibliographic record
Abstract
Integration of wireless and optical access technologies for the Internet access seems as a promising solution to reduce the cost of deploying fiber to the premises. Wireless Optical Broadband Access Network (WOBAN) combines wireless mesh and optical communication technologies at the front and the back ends of the Internet access, respectively. Survivable design of both ends of WOBAN occurs as an important problem for the network operators. In this paper, we propose a restoration framework for WOBAN which is inherited from a previously proposed architecture. Our proposed scheme attempts to select optimum number of protection clusters for the WDM-PON segments at the back-end of WOBAN considering the optimum deployment of the fibers between the backup ONUs so that the restored traffic propagates with the minimum delay. Optimization results show that our proposed scheme leads to shorter fiber deployment between the ONUs which enables the failed traffic to propagate faster to the feeder fiber. Moreover, taking the advantage of the ring protection also provides the proposed scheme to cover the whole traffic in a failure-impacted WDM-PON segment.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".