Building robust and decentralized tactical name services with JXTA: Performance issues and solutions
Bibliographic record
Abstract
Discovering tactical resources (a.k.a. name service or service discovery) in a robust, decentralized, and scalable fashion is critical for the success of tactical communications, particularly in dismounted segments consisting of dismounted soldiers/sensors and mounted segments formed by combat and support vehicles, combat Headquarters (HQ) and Command Post (CP). JXTA-the de facto standard of P2P programming frameworks-offers a promising open-source technology for building such a tactical name service. However, since JXTA is primarily built for Internet based P2P applications, we face several challenging issues in adapting this open-source technology to tactical networks for the tactical name service. In this paper, we identify algorithmic deficiencies in the JXTA 2.0 reference implementation and propose novel algorithms to overcome the deficiencies in tactical networks. We show through simulation that the proposed algorithms achieve much better lookup performance and consume lower bandwidth than the ones implemented in the JXTA 2.0 reference implementation under tactical networking scenarios.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".