Analysis of OpenFlow and NETCONF as SBIs in Managing the Optical Link Interconnecting Data Centers in an SDN Environment
Bibliographic record
Abstract
SDN technology has primarily been applied to all types and size of network ranging from Ethernet services to large cloud environment.More recently, interest has turned towards extending programmability of the OTN.In the SDN architecture, SBIs are used to communicate between the SDN controller and the switches or routers in the network.In this thesis we deploy two major protocols as SBIs in managing BoD across the interconnected data centers over the OTN.The OpenFlow and NETCONF are the two SBIs deployed between the OpenDayLight controller and the BTI7800 optical edge transponders.We present the OpenVSwitch architecture modified for referencing the optical ports of the BTI7800 devices.Experimental demonstration and performance of both BTI YANG-based NETCONF and OpenFlow protocols are presented.Our experiments show that NETCONF is faster and efficiently handles the control message; whereas in a fully loaded system, OpenFlow offers better bandwidth utilization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".