Skipping technique in face routing for wireless ad hoc and sensor networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Greedy routing and face routing route data by using location information of nodes to solve scalability problem incurred in table-driven routing. Greedy routing efficiently routes data in dense networks, but it does not guarantee message delivery. Face routing has been designed to achieve guaranteed message delivery. Face routing, however, is not efficient in terms of routing path length. In this paper, we present a Skipping Face Routing (SFR) protocol to reduce the face traversal cost incurred in the existing approaches. In SFR, we specify a set of sufficient conditions so that each node can determine if it can skip some intermediate nodes during face traversing based solely on the neighbour information of the node, resulting in reduced total number of transmissions. By using simulation studies, we show that SFR significantly reduces the communication cost and traversal time required in face traversal compared with the existing approaches.
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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 | 0.000 | 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 it