Joint routing, scheduling, and network coding for wireless multihop networks
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 paper presents a study on achievable throughput in wireless multihop networks with unicast flows that use XOR-like network coding. A joint routing, scheduling, and network coding problem is formulated under a realistic signal to interference plus noise ratio interference model. This formulation provides a mathematical framework to study the achievable throughput of a given wireless network for a given utility function. We optimally solve it for max-min throughput in small to medium size networks by developing an efficient computation tool. Our numerical results show that throughput gains can be obtained at low transmission powers by using simple XOR-like network coding in a mesh-like network provided it is optimally configured in terms of routing, scheduling, and network coding but that they are only significant (i.e., greater than 15%) for some special cases. We also compute max-min throughput by restricting network coding to some key nodes or flows to quantify key conditions that provide a significant portion of gains.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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