Energy Aware Scheduling and Routing of Periodic Lightpath Demands in Optical Grid Networks
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Bibliographic record
Abstract
Optical grid networks provide an ideal infrastructure to support large-scale data intensive applications and interconnection of data centers. The power consumption of communications equipment for such networks has been increasing steadily over the past decade and energy efficient routing schemes and traffic models can be utilized to reduce the energy consumption. In many applications it is possible to select the destination node from a set of possible destinations, which have the required computing/storage resources. This is known as anycasting. We propose a novel formulation that exploits knowledge of demand holding times and the flexibility of anycast routing to optimally schedule demands (in time) and route them in order to minimize overall network energy consumption. Our simulation results demonstrate that the proposed approach can lead to significant reductions in energy consumption, compared to traditional routing schemes.
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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 | 0.001 |
| 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