A novel signaling nested reservation protocol for all-optical networks
Bibliographic record
Abstract
This work proposes a new reservation protocol for enhancing the performance of wavelength-routed networks. To be more robust and reliable, the proposed approach employs distributed control mechanisms. The new method particularly focuses on wavelength-division multiplexed (WDM) core networks with distant end-nodes. It takes into account the considerable amount of data that can be transferred by high-speed WDM networks within limited reservation periods. To increase the throughput, the protocol consumes the unoccupied bandwidth of reservation phases by transferring nonreal-time data packets during these intervals. This scheme is implemented by applying a modified form of backward reservation protocol. To initiate a multihop reservation call, this protocol labels a path as reserved instead of locking it. Meanwhile, labeled nodes with single-hop requests will receive permission signals to send predetermined packet sizes. The length of packets transmitted is defined by the round-trip propagation delay between the current and the upcoming nodes along the path. In case a reservation fails, already labeled nodes will be notified by receiving a prevention signal, which will block them from transferring data packets.
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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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".