Modeling of Loosely Coupled Scatternets with Finite Buffers
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
This article deals with the performance of Bluetooth scatternets in a real-life environment where different queues are implemented with finite buffers. Finite buffer size will introduce packet blocking at different queues along the packet path, which in turn causes changes in effective traffic load as well as retransmissions and ultimately affects end-to-end packet delays. The authors assume that the piconet masters use E-limited intra-piconet polling, while bridge scheduling is performed using the walk-in approach without rendezvous points. They present a detailed simulation model that allows them to obtain accurate measurements of blocking probabilities, end-to-end-packet delays, and overall throughput in the network as functions of network and device parameters. Some practical recommendations about the buffer size that will keep the blocking probability within reasonable limits are also given.
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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