Bibliographic record
Abstract
Wireless mesh networks (WMNs) have recently gained a lot of popularity due to their rapid deployment and instant communication capabilities. However, as a key technology for next-generation wireless networking, WMNs lack suitable routing metrics and protocol for new features. Currently, AODV is the routing protocol used in WMNs. This paper proposes an ants-in-mesh (AIM) routing protocol for wireless mesh networks, which is based on ideas from the nature-inspired ant colony optimization (ACO) framework. AIM agent distributes forward ants on demand to search for the routes to the destination and then activates corresponding backward ants to confirm the routes and update the pheromone. AIM enables only the destination to choose k multiple paths based on ants pheromone, which is based on several link-relevant quality of service (QoS) metrics. AIM agent maintains status of local links by exchanging hello messages periodically. Simulation results show that AIM outperforms AODV in terms of packet delivery ratio and total end-to-end delay.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".