Analysis of priority arbitration in low‐rate CSMA/CA‐based differentiated access with throughput optimization
Bibliographic record
Abstract
Summary A class of applications, such as home energy management and control and utility data acquisition, is emerging in recent times where smart meters, sensors, and appliances are networked together for intelligent management and coordination. Such applications rely on low data rate communication of monitoring and control information at large scale. For the underlying networking infrastructure to facilitate communication of the real‐time and intermittent packet traffic expected, random access‐based protocols are regarded as suitable medium access control solutions. A key challenge in this regard is that the random access protocols are prone to throughput degradation when the number of contending nodes grows, as expected with the infrastructures involved. Besides, provision for certain degree of criticality/priority is needed for some of the packets compared with the rest. With this background, this paper analytically determines the criterion for throughput‐optimal operations in a network based on low‐rate carrier sense multiple access protocol. In addition, ways to provide priority‐wise access differentiation at arbitrary proportions without a negative impact on the achievable throughput is incorporated within a binary exponential backoff ‐ based collision avoidance scheme. Discrete‐event simulations are performed to validate the accuracy of the approximations made in analysis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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".