An integrated TDM architecture for AAPN networks
Why this work is in the frame
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Bibliographic record
Abstract
The Agile All-photonic Backbone Network (AAPN) architecture has been proposed by the telecommunication industry as a potential candidate for the ultra high speed Next Generation Optical Network (NGON) architecture. AAPN network structure is composed of adaptive optical core switches and edge routers in an overlaid star physical topology. The AAPN employs fast packet switching architecture for the network traffic, and the packet scheduling is the main part of the AAPN. The objective is to forward the packets to their destination with the lowest drop rate and delay, the bandwidth allocation can be either located at the core node or the edge switch. Two types of scheduling are considered in the AAPN architecture, namely the <i>centralized</i> and the <i>distributed</i> schemes. In the centralized scheme all decisions are made at the core node while in the distributed scheme, they are made at the edge nodes. In this paper, we want to compare both scheduling schemes. We would also like to propose a promising integrated TDM architecture that combines the good attributes of both centralized and distributed scheduling schemes. We shall characterize such architecture by various measures such as delay and loss probabilities.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it