CLIP: Centrality-Led ILP Controller Placement for Software-Defined Networking
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
Software-Defined Networking (SDN) revolutionizes network architectures by decoupling control and data planes, with controller placement critically impacting performance metrics. While existing state-of-the-art approaches focus on heuristic solutions or single-objective optimization for the Controller Placement Problem (CPP), this study advances the field through a rigorous mathematical formulation integrating both topological characteristics (distance matrices) and network centrality measures (betweenness centrality). We propose CLIP, an integer linear programming (ILP)-based solution that simultaneously optimizes for latency reduction, reliability enhancement, and number of controllers, addressing key limitations in current solutions. Experimental validation demonstrates that our SDN-enabled framework outperforms conventional legacy networks by 49.92-51.60% in latency reduction, while maintaining comparable deployment costs. These results establish a new benchmark for CPP optimization, particularly in scenarios requiring balanced multi-objective decision-making under real-world constraints. The findings provide network architects with a principled methodology for SDN deployment that surpasses current industry standards.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 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 it