Joint congestion control and distributed scheduling for throughput guarantees in wireless networks
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Bibliographic record
Abstract
We consider the problem of throughput-optimal cross-layer design of wireless networks. We propose a joint congestion control and scheduling algorithm that achieves a fraction 1/ d I ( G ) of the capacity region, where d I ( G ) depends on certain structural properties of the underlying connectivity graph G of the wireless network, and also on the type of interference constraints. For a wide range of wireless networks, d I ( G ) can be upper bounded by a constant, independent of the number of nodes in the network. The scheduling element of our algorithm is the maximal scheduling policy. Although this scheduling policy has been considered in several previous works, the challenges underlying its practical implementation in a fully distributed manner while accounting for necessary message exchanges have not been addressed in the literature. In this article, we propose two algorithms for the distributed implementation of the maximal scheduling policy accounting for message exchanges, and analytically show that they still can achieve the performance guarantee under the 1-hop and 2-hop interference models. We also evaluate the performance of our cross-layer solutions in more realistic network settings with imperfect synchronization under the Signal-to-Interference-Plus-Noise Ratio (SINR) interference model, and compare with the standard layered approaches such as TCP over IEEE 802.11b DCF networks.
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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