A Reliable IEEE 802.15.4 Model for Cyber Physical Power Grid Monitoring Systems
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
Cyber physical systems (CPSs) can significantly improve the resiliency of the smart grid. In CPSs, real time and reliable monitoring require an accurate and stable model of the wireless sensor network (WSN)-based monitoring system. Furthermore, WSNs require strict quality of service (QoS) provisioning as the data generated by the monitored equipment is generally delay and reliability-sensitive. QoS provisioning in WSNs has been widely studied in the literature where most of the work addresses the issue by QoS-aware protocol design. However, analytical models that consider delay, throughput, and power consumption have not matured for CPSs. In this paper, we propose a Markov-based model for cluster-tree WSN topologies that enhances the stability of the WSNs. Cluster-tree deployments are particularly of interest to cyber-physical power grid monitoring systems since they are suitable for large-scale deployments. We perform an exhaustive performance evaluation using different traffic and network conditions in star and cluster-tree WSN topologies. Furthermore, we test the accuracy of our model by performing simulations in environments that are consistent with the analytical model.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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