Using simulation to evaluate traffic engineering management services in maritime networks
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
One of the critical problems in maritime tactical networks is how to maximize the Quality of Service (QoS) achieved by critical traffic while dealing with mobile and limited-capacity links. As part of a research effort to provide enhanced communications capabilities in a maritime tactical network, a number of traffic-engineering techniques have been investigated using the OPNET discrete-event simulation (DES) tool. In this paper, we describe the model developed to simulate the maritime environment and the impact on network traffic of three traffic-engineering based management services: first, a traffic-monitoring service matches the amount of traffic it produces with its knowledge of the current load of the network; second, a traffic-prioritisation service uses weighted fair queuing (WFQ) to prioritize critical traffic; and finally, an adaptive-routing service uses multi-path labelled switching (MPLS) to divert traffic from overloaded links. The effect of these services on network traffic has been simulated and the results are described in this paper.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it