A Hierarchical P2P Overlay for Hierarchical Mobile Ad hoc Networks (MANETs)
Bibliographic record
Abstract
P2P applications deployment on MANETs is motivated by the popularity of these applications, coupled with the widespread use of mobile devices. P2P applications and MANETs have common features such as decentralization, self organization, and the absence of dedicated servers or infrastructure. The deployment often faces specific performance challenges resulting from topological overlay and underlay mismatch, limited bandwidth constraint and dynamic topology changes. Hierarchical MANETs are a special type of MANETs where some nodes have specific routing roles to allow inter- cluster communications. Such topologies (typical for tactical networks) render a successful P2P deployment more challenging. We developed a novel approach for P2P deployment in such networks by bringing topology-awareness into the overlay, mapping the underlay topology (structure) to the logical overlay and building a hierarchically-structured logical overlay on top of the hierarchical underlay. Simulation results demonstrated a significant performance advantage of our proposed deployment solution vs. a flat logical overlay using different configurations and mobility 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".