Probabilistic Availability Quantification of PON and WiMAX Based FiWi Access Networks for Future Smart Grid Applications
Bibliographic record
Abstract
Availability is one of the most important quality attributes for smart grid communications, as qualitatively defined in the IEEE P2030 standard. However, the availability metric must be quantified to validate given smart grid application requirements. In recent related work, availability has been quantified for wireless and optical backhaul networks in terms of communications reachability, while in some other work availability was not formally defined in a fine-grained manner and was assumed to be known. In this paper, we develop a novel multi-class probabilistic availability model for integrated passive optical network (PON) and WiMAX networks to quantify this metric according to medium access control (MAC) protocol limits as well as fiber and base station failures. The obtained numeric results show interesting availability behaviors, including the impact on availability depending on the number of base stations. We also investigate optical traffic re-routing through WiMAX when fiber faults occur and show that there exists a maximum amount of re-routed traffic for maximizing availability. Furthermore, we investigate a scenario of real-world smart grid traffic configurations shared with regular traffic and find the maximum sensor data rate to meet the availability requirements.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".