Ant colony-based many-to-one sensory data routing in Wireless Sensor Networks
Bibliographic record
Abstract
An ant colony-based routing protocol is presented in this paper that is specifically designed to route many-to-one sensory data in a multi-hop Wireless Sensor Network (WSN). Because a many-to-one routing paradigm generates lots of traffic in a multi-hop WSN resulting in greater energy wastage, higher end-to-end delay and packet loss, the proposed routing protocol also comes with a lightweight congestion control mechanism, which is capable of handling both event-based and periodic upstream sensory data flow to the base station. The proposed protocol works in two-phases. During the first phase, the protocol uses ant-based intelligence to find and enforce the shortest path and in the second phase, when the actual many-to-one sensory data transmission takes place, the protocol combines the knowledge gained during the first phase with the congestion control mechanism to avoid packet loss and traffic while routing the sensory data. When compared with the related algorithms, the proposed algorithm shows promising results.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".