A framework for distributed provisioning availability-guaranteed least-cost lightpaths in WDM mesh networks
Bibliographic record
Abstract
The trend in the development of intelligent optical networks is the move towards a unified solution, to support voice, data, and various services. Nowadays, different applications may need different levels of protection and differ in how much they are willing to pay for the service they get. A control scheme which is used to set up and tear down lightpaths, should not only be fast and efficient, but also be scalable. In addition, it should also try to minimize the connection cost and the number of blocked connections while satisfying the requested level of availability. In this work we choose the availability of a connection as a quality of service (QoS) parameter to denote different levels of protection. It is proven that the Availability-Guaranteed least-cost (AGLC) routing problem is NP-complete. We propose a distributed control scheme based on parallel fixed alternative routing approach for establishing AGLC lightpaths. The proposed framework performance is studied through extensive simulation experiments on wavelength selective network with different traffic loads. The simulation results show that our proposed framework provides better performance in terms of average blocking probability, and average routing distance average path cost.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".