Studying the impact of web-services implementation of distributed simulation of DEVS and Cell-DEVS models
Bibliographic record
Abstract
DEVS is a Modeling and Simulation formalism that has been used to study the dynamics of discrete event systems. Cell-DEVS is a DEVS-based formalism that defines the cell space as a group of DEVS models connected together. This work presents the design and implementation of a distributed simulation engine based on CD++; a modeling and simulation toolkit capable of executing DEVS and Cell-DEVS models. The proposed simulation engine follows the conservative approach for synchronization among the nodes, and takes advantage of web service technologies in order to execute complex models using the resources available in a grid environment. In addition, it allows for the integration with other systems using standard web service tools. The performance of the engine depends on the network connectivity among the nodes; which can be commodity Internet connections, or dedicated point-to-point links created using User Controlled Light Path (UCLP). UCLP is a web service-based network management tool used by grid applications to allocate bandwidth on demand. 1.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".