A redistribution scheme centred on communication delay for distributed virtual simulations
Bibliographic record
Abstract
Communication latencies directly influence the performance of distributed virtual simulations due to existent dependencies between simulation elements. The High Level Architecture (HLA) was designed to organize these simulations and reduce communication overhead. Even though the framework successfully manages data distribution, it is not concerned of communication distances and the network topology, which generate mostly of the delays in simulations. In order to provide a solution for organizing distribution simulations according to communication aspects, many approaches have been proposed. The approaches that provide a broader solution consider the proximity of resources in their redistribution algorithms. Even though these schemes considerably improves simulation performance, they are based on static characteristics of networking resources. Thus, a redistribution scheme is proposed to include communication delay as the main balancing metric and to detect the dynamic changes in systems' communication load. Experiments have been performed to compare the proposed scheme with the previous distributed scheme and to determine the effectiveness of using delay for balancing HLA-based simulations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".