Increasing packet delivery ratio in DSR by link prediction
Why this work is in the frame
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Bibliographic record
Abstract
Most existing on-demand mobile ad hoc network routing protocols continue using a route until a link breaks. During the route reconstruction, packets can be dropped, which will cause significant throughput degradation. In this paper, we add a link breakage prediction algorithm to the dynamic source routing (DSR) protocol. The mobile node uses signal power strength from the received packets to predict the link breakage time, and sends a warning to the source node of the packet if the link is soon-to-be-broken. The source node can perform a pro-active route rebuild to avoid disconnection. Experiments demonstrate that adding link breakage prediction to DSR can significantly reduce the total number of dropped data packets (by at least 20%). The tradeoff is an increase in the number of control messages by at most 33.5%. We also found that the proactive route maintenance does not cause significant increase in average packet latency and average route length. Enhanced route cache maintenance based on the link status can further reduce the number of dropped packets.
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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 | 0.001 | 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 | 0.001 |
| 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