QoS-driven MAC-layer resource allocation for wireless mesh networks with non-altruistic node cooperation and service differentiation
Why this work is in the frame
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Bibliographic record
Abstract
Node cooperation has been demonstrated promising in system performance improvement for wireless networks. To effectively provision packet-level quality-of-service (QoS) in wireless mesh networks (WMNs) supporting heterogeneous traffic, medium access control (MAC) with service differentiation is imperative. In this paper, we study the problem of non-altruistic non-reciprocal node cooperative resource allocation for WMNs with QoS support, taking subcarrier allocation, power allocation, partner selection/allocation, service differentiation, and packet scheduling into account. Due to the NP hardness of our resource allocation problem, we propose two low-complexity yet effective approaches based on the Karush-Kuhn-Tucker (KKT) interpretations, tailored for WMNs with QoS assurance and MAC-layer service differentiation. Further, simulation results show that both proposed approaches can effectively provision packet-level QoS and enhance system performance. Our study also sheds some light on the question of whether and when non-altruistic node cooperation is beneficial to WMNs.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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 it