Distributed Routing Schemes with Accessibility Consideration in Multi-Hop Wireless Networks
Bibliographic record
Abstract
In this paper, two novel distributed routing schemes, named adaptive-information-moving-rate routing scheme (AIMR) and adaptive-information-moving-distance-and-link-rate routing scheme (AIMDLR), are proposed for multi-hop wireless networks by jointly considering the number of hops and the link states. With one-hop information only, both schemes aim at improving the network spectral efficiency under two different bandwidth sharing methods (i.e., throughput-maximization bandwidth sharing and equal-time bandwidth sharing), respectively. In addition, a general scheme, called probability-based scheme (PBS), is proposed to improve the accessibility of distributed routing schemes, which is denoted by the success probability of finding a route reaching the destination. In the PBS, the node selection in each hop is based on a well-defined probability, which takes into account the locations of the transmitter and the receiver at each hop and the uncertainty in the subsequent hops. By combining the PBS with the AIMR and the AIMDLR, the proposed probability-based AIMR (PAIMR) and probability-based AIMDLR (PAIMDLR) can not only improve the accessibility significantly but also achieve higher effective spectral efficiency compared to the counterparts. Simulation results are finally presented to demonstrate the advantages of the proposed routing schemes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".