Partial Delaunay Triangulations Based Data-Centric Storage and Routing with Guaranteed Delivery in Wireless Ad Hoc and Sensor Networks
Bibliographic record
Abstract
Existing memory-less greedy-face-greedy (GFG) routing algorithm can guarantee the delivery in wireless ad hoc networks modeled by a connected unit disk graph. The FACE mode in GFG routing is a recovery mode used when no neighbor closer to destination exists. Face mode requires extracting a planar sub graph out of the unit disk graph. In this paper, we propose to apply partial Delaunay triangulation (PDT) instead of Gabriel graph (GG) used in the original GFG routing. PDT is locally defined without any message exchange in addition to those needed to learn locations of neighbors. This appears to be the densest known such message free planar graph. PDT can be used instead of GG for storing data in wireless sensor networks, where each datum is stored in the face of PDT containing hashed location of datum. Simulation results show the GFG routing has better performance on a PDT than on a GG, since PDT is denser than GG. Applying dominating set based routing or a shortcut scheme can further enhance the PDT-based routing performance.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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 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".