Towards Enabling Fault Tolerance and Reliable Green Communications in Next-Generation Wireless Systems
Bibliographic record
Abstract
Green communications have witnessed significant attention being paid to the next generation of wireless systems research and development. This is due to growing use of sensor- and battery-oriented smart wireless devices. The related literature in green communications for next-generation wireless systems majorly relies on transmission and sensing power management, but lacks a fault-tolerant centric approach. In this context, this paper presents a fault-tolerant and reliable green communications framework for next-generation wireless systems (FRGNWS). Firstly, maximum node-disjoint routes from all source nodes to the base station are identified based on the hybrid adapted grey wolf sine cosine optimizer. Secondly, a fault-tolerant and reliable route is selected from the maximum disjoint routes for each sensor node to the base station based on the hybrid adapted grey wolf whale optimizer. The performance of our proposed green communications framework is assessed by simulation experiments considering a realistic implementation scenario and different metrics. Simulation results clearly validate the efficacy of the proposed green communications framework as compared to the state-of-the-art techniques.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".