An Efficient Time Management Scheme for Large-Scale Distributed Simulation Based on JXTA Peer-to-Peer Network
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Bibliographic record
Abstract
As an emergence technology, P2P is spreading to distributed simulation area, and many distributed simulation frameworks have used P2P as the middleware to interconnect their existing single processor's simulators to form distributed environments for simulation execution. In terms of simulation time management, most existing tools use a middleware layer to implement and support time management in a heterogeneous networking environment, and therefore, it is generally not easy to migrate a single processor's simulation to multi-processors in these frameworks. In this paper, we present a P2P based distributed simulation time management based upon JXTA API and Service Oriented Architecture (SOA), and we focus our discussion on how we implement the time management as a JXTA peer and a JXTA group service. Our time management is actually a native distributed message passing management framework, and does not rely on any middleware layer. Furthermore, we evaluate the performance of our implementations using a local Linux cluster. This work will establish a solid foundation for the more advanced distributed simulation services that have been proposed in our project [1].
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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 | 0.001 | 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 | 0.000 |
| 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)
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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