Passive and greedy beaconless geographic routing for real-time data dissemination in wireless networks
Bibliographic record
Abstract
Real-time geographic routing is one of the most popular examples relying on a greedy algorithm to deliver real-time data in wireless networks. Each sender node decides a next-hop node among one-hop neighbours in stateless manner. However, this sender-side decision paradigm suffers from periodic and network-wide beaconing to discover neighbour nodes. To overcome the limitation, this paper suggests a passive and greedy beaconless real-time routing, called PGBR. To forward real-time data by receiver-side selection, PGBR focuses on two major challenging issues: a delay estimation procedure and a contention function design. The delay estimation procedure estimates both waiting delay and packet transmission delay used for the contention function. PGBR also redesigns receiver-side contention function with deliberating the estimated delay and discuss combinations of important metrics for the contention. The experimental results show that PGBR could improve the energy-efficiency as well as keeps high delivery deadline success ratio.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".