A novel distributed progressive reservation protocol for WDM all-optical networks
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Bibliographic record
Abstract
In this paper, we propose and describe a new distributed reservation protocol for establishing lightpaths in WDM all-optical networks. Distributed control mechanisms are preferred and employed because of their advantages over centralized ones to set up virtual channels. The new protocol is a combination of the conservative and aggressive backward reservation protocols, which attempts to improve performance by adapting a reservation to network circumstances. On the one hand, the new protocol uses network circumstances and decides and applies a more conservative or aggressive approach. In other words, the protocol progressively fluctuates between those reservation protocols in order to capture their respective advantages. As a result, in extreme cases it acts exactly like either the conservative or the the aggressive reservation protocol. On the other hand, it considers the characteristics of a network to set a retry-list size. As a result, a retry-list size is not determined by a fixed number but modified based on the multiplexing degree of a network, which prevents imposing ineffective retries on a network with a small number of wavelengths and instead encourages more retries for a network with numerous channels. Therefore, the proposed protocol transforms the static nature of existing reservation protocols into a more adaptive one in order to enhance network performance.
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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 it