Survivable traffic grooming with non‐service‐interruptive wavelength retuning in a WDM mesh network
Bibliographic record
Abstract
Abstract This paper proposes a new survivable traffic grooming wavelength retuning (STGWR) scheme in an all‐optical wavelength division multiplexing (WDM) network. In a dynamic WDM network, a connection may require a bandwidth less than a wavelength capacity. In addition, a connection should be protected against any network failures. Survivable traffic grooming (STG) can protect connections at subwavelength granularities. Wavelength retuning is a promising approach in an all‐optical WDM network, where a signal must remain on the same wavelength from its source to the destination, to alleviate the wavelength continuity constraint and reduce the connection blocking probability. Although both STG and wavelength retuning have attracted extensive research attentions nowadays, no effort has been made to combine these two promising approaches in one network. In this paper, we propose a wavelength retuning scheme with no service interruption in an all‐optical network with STG capability. The scheme allocates two routes, one for the active path and other for the backup path, in a shared mesh restoration manner to each incoming connection request and conducts wavelength retuning only on the backup path. Both wavelength retuning and mesh protection are done at the connection level instead of at the lightpath level. The simulation results of the proposed schemes are also presented. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".