Abstract ACO-EEAODR: An Ant-Swarm Inspired Energy-Efficient Ad Hoc On-Demand Routing Protocol for Mobile Ad Hoc Networks
Bibliographic record
Abstract
As the world’s economic activities are expanding, the energy comes to the fore to the question of the sustainable growth in all technological areas, including wireless mobile networking. Energyaware routing schemes for wireless networks have spurred a great deal of recent research towards achieving this goal. Recently, an energy-aware routing protocol for MANETs (so-called energy-efficient ad hoc on-demand routing protocol (EEAODR) for MANETs was proposed, in which the energy load among nodes is balanced so that a minimum energy level is maintained and the resulting network lifetime is increased. In this paper, an Ant Colony Optimization (ACO) inspired approach to EEAODR (ACO-EEAODR) is proposed. To the best of our knowledge, no attempts have been made so far in this direction. Simulation results are provided, demonstrating that the ACO-EEAODR outperforms the EEAODR scheme in terms of energy consumed and network lifetime, chosen as performance metrics.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".