A Markov-Modulated End-to-End Delay Analysis of Large-Scale RF Mesh Networks With Time-Slotted ALOHA and FHSS for Smart Grid Applications
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Bibliographic record
Abstract
A new mathematical model and methodology are proposed to evaluate the performance of large-scale RF-mesh networks that use time-slotted ALOHA with frequency hopping spread spectrum. This type of architecture is quite usual in advanced metering infrastructures. An analytic formulation for the delay, based on Markov-modulated modeling of the system, is derived. The formula can be extended to evaluate other important performance metrics. The proposed methodology is applied to a large scale network of several thousands of nodes, and numerical results are reported to show the wide variety of performance evaluations that are enabled. The usefulness of the assessment of the feasibility of different types of applications (e.g., smart-metering and sensor networks) is shown. An analysis of the scalability of this methodology and a comparison with simulation results are also presented.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it