Distributed SDN Controller Placement Using Betweenness Centrality & Hierarchical Clustering
Bibliographic record
Abstract
Software-defined networking (SDN) separates the control plane from the data plane. This simplifies network management and provides flexibility to the network administrator. Such an architecture can be implemented in various types of networks including wide-area networks and vehicular networks. Two different approaches are possible for the control plane, namely the centralized controller approach and the distributed multiple controllers approach. For efficient network management in a large distributed network, the location and number of controllers should be optimized to provide the service providers desired system performance. This paper proposes a new framework that solves the SDN controller placement problem by combining both the hierarchical clustering and betweenness centrality concepts (denoted as HC-BC). The performance of the proposed framework is evaluated using a real-world network and compared to three other algorithms in terms of worst-case switch-to-controller latency and domain imbalance. The simulation results show that the proposed HC-BC framework achieves the best compromise between the latency and the domain imbalance between different clusters, with the added advantage of having lower computational complexity.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".