Stochastic delay guarantees and statistical call admission control for IEEE 802.11 single-hop ad hoc networks
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Bibliographic record
Abstract
This paper presents a new approach to provide stochastic delay guarantees via fully distributed model-based call admission control for IEEE 802.11 single-hop ad hoc networks. We propose a novel stochastic link-layer channel model to characterize the variations of the channel service process in a non-saturated case using a Markov-modulated Poisson process (MMPP) model. We use the model to calculate the effective capacity of the IEEE 802.11 channel. The channel effective capacity concept is the dual of the effective bandwidth theory. Our approach offers a tool for distributed statistical resource allocation in ad hoc networks, which combines both efficient resource utilization and quality-of-service (QoS) provisioning to a certain probabilistic limit. Simulation results demonstrate that the MMPP link-layer model and the calculated effective capacity can be used effectively in allocating resources with stochastic delay guarantees.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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