Routing via Functions in Virtual Networks: The Curse of Choices
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
An important evolution of the users’ needs is represented by the on-demand access to the network, storage, and compute resources in order to dynamically match the level of resource consumption with their service requirements. The response of the network providers is to transition to an architecture based on softwarization and cloudification of the network functions. This is the rationale for the deployment of network functions virtualization (NFV) where virtual network functions (VNFs) may be chained together to create network services. Efficient online routing of demand across nodes handling the functions involved in a given service chain is the novel problem that we address in this paper. We provide an original formulation of this problem that includes link and CPU capacity constraints and is based on the construction of an expanded network. We derive the exact mathematical formulation and propose several heuristic algorithms taking into account the main system’s parameters. We conclude by deriving some interesting insights both about the algorithms and the network performance by comparing the heuristics with the exact solutions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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