Analytic modeling of CSMA/CA based differentiated access control with mixed priorities for smart utility networks
Bibliographic record
Abstract
A stochastic model is presented in this paper for packet-level performance analysis of the medium access control (MAC) schemes considered for adoption in smart utility networks. Smart grid communications involve critical issues in terms of reliability and timeliness, and the MAC largely determines efficiency of packet-level communication within the immediate neighborhood. Powerline communication (PLC), a relatively old communication technology, has reemerged in recent times, and is regarded as one of the key enablers in smart grid communication. The analytic problem addressed in this paper is formulated in light of the distinctive characteristics of some of the PLC based MAC schemes, and also relevant to smart grid utility networks, e.g., low data rate CSMA/CA with access differentiation. Specifically, with consideration of two classes of packets, this paper investigates basic performance metrics such as throughput and packet service time in view of the effectiveness of the access differentiation mechanisms. The evaluation shows that with increase in the number of contending nodes, strong discrimination between the classes persists in medium access opportunities though both aggregate and class-wise throughputs degrade.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".