Software-defined DWDM optical networks: OpenFlow and GMPLS experimental study
Bibliographic record
Abstract
Finding an effective and simple unified control plane (UCP) for IP/Dense Wavelength Division Multiplexing (DWDM) multi-layer optical networks is very important for network providers. Generalized Multi-Protocol Label Switching (GMPLS) has been in development for decades to control optical transport networks. However, GMPLS-based UCP for IP/DWDM multi-layer networks is extremely complex to be deployed in a real operational products because still there are a lot of non-capable GMPLS equipments. DRAGON (Dynamic Resource Allocation via GMPLS Optical Networks) [1] is a software that solves this issue making these equipments capable for working in a GMPLS network. On the other hand, OpenFlow (OF), one of the most widely used SDN (Software Defined Networking) implementations, can be used as a unified control plane for packet and circuit switched networks [2]. In this paper, we propose and experimentally evaluate two solutions using OpenFlow to control both packet and optical networks (OpenFlow Messages Mapping and OpenFlow Extension). These two solutions are compared with GMPLS-based UCP. The experimental results show that the OpenFlow Extension solution outperforms the OpenFlow Messages Mapping and GMPLS solutions.
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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 | 0.001 | 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 | 0.001 |
| 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 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".