A distributed controller for a virtualized router
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this paper, a distributed controller for a virtualized router is proposed. This controller enables the dynamic and automatic resource allocation between the different virtual routers (called slices) running on top of the physical router. The controller is designed on a two-layer architecture. A slice controller (one for each slice) estimates the relationship between the past performances and resource allocations of the slice using a linear model, and then determines the requested allocation for the slice to meet its target performance. The physical router consists of a set of modular linecards. A resource controller (one for each linecard), collects the resource allocation requests from the different slices using the resources it controls and determines the allocations based on the available capacities of the resources. Resources are allocated to slices to guarantee their target performances if possible, or provide service differentiation if the total requests from all the slices exceeds the capacities of the shared resources. We have found that the convergence of the controller depends on different parameters (such as the number of slices and the parameters of the linear model) and therefore some tuning of these parameters is needed for the system to achieve the stability.
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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 | 0.000 |
| 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