A technology study on tactical naming service for mounted and dismounted segments
Bibliographic record
Abstract
Tactical naming service is a critical component of tactical communications systems, which provides essential name-address resolution and service discovery for tactical users. Generally speaking, tactical users of land communications systems can be categorized into stationary HQ users (users in headquarters network), mounted users (users in vehicle networks), and dismounted users (users in mobile ad hoc networks). The greatest technical challenge facing the tactical naming services stems from dynamic and mobile nature of these mounted and dismounted segments (MDS) with low-bandwidth and/or unreliable communication links. Traditional DNS is part of the problem space rather than a solution because DNS server has to be dynamically discovered for all remote clients through the tactical naming service in the first place. Zeroconf solutions such as multicast DNS (mDNS) and link-local multicast name resolution (LLMNAR) and distributed hash table (DHT) based solutions offer potential remedy for MDS. Since these technologies are originally conceived for the internet and commercial network domains, feasibility of applying these technologies into MDS still remains elusive. In this paper we evaluate multicast query and DHT based solutions from a tactical perspective through analytic modelling and simulation and give quantitative measures regarding their limitations. Based on analysis of these existing technologies we present a hybrid naming service approach that fits into the whole spectrum of MDS.
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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 | 0.000 |
| 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 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".