Comparative analysis of software defined networking (SDN) controllers — In terms of traffic handling capabilities
Bibliographic record
Abstract
Software Defined Networking (SDN) is an emerging paradigm that allows network operators to have more control of their infrastructure. Control is achieved by decoupling control and data plane of the network. Controller is the place where all the intelligence of SDN resides; hence it is important to test the capabilities of the controller before deploying it in production networks. This paper presents an analysis of the capabilities of two open-source python based OpenFlow SDN controllers (POX and RYU). The analyzed indexes include performance of both the controllers when subjected to layer 1 and layer 2 switching. For testing purposes Mininet emulator and Distributed-Internet Traffic Generator (D-ITG) traffic generator are used. The results of the evaluation, when layer 1 switching is in question, show, that POX has better traffic handling capabilities, and, as a result, a better performance. But, as far as layer 2 switching is concerned, RYU came up with far better performance results.
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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) | 0.001 | 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 | 0.000 |
| 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".