Ant Colony Optimization (ACO) Based MANET Routing Protocols: A Comprehensive Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Application of mobile ad hoc networks (MANETs) has gained significant popularity among researchers in the field of data communication networks. However, a MANET operating in a wireless environment imposes a number of challenges for the implementers so far as routing of packets across it is concerned. There is a wide range of research contributions are available in the literature wherein authors propose various solutions to overcome the problems and bottleneck related to routing in MANET. Especially soft computing techniques and Ant Colony Optimization (ACO) in particular has been significantly popular among the researchers to resolve MANET routing issues. This technique plays a vital role in route discovery in particular. In this paper, we have conducted a comprehensive review of this technique applied to routing in MANET with respect to various criteria. Hopefully this paper serves to a perfect document for researchers in this field.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.002 | 0.001 |
| 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