Flow Starvation Mitigation for Wireless Mesh Networks
Bibliographic record
Abstract
Wireless mesh networks can provide scalable highspeed Internet access at a low cost. Fair channel access among different nodes in the wireless mesh network, however, is an important consideration that needs technological solutions before mesh networks can be widely deployed. Lack of fairness significantly decreases the throughput of nodes that are more than one hop away from mesh gateways. We propose an analytical model and use simulation studies to establish the existence of starvation in mesh networks even when we can ameliorate problems due to exposed terminals. Motivated by the inability of standard medium access control (MAC) protocols to limit starvation, we propose a modification to the MAC protocol to alleviate flow starvation. Our proposed algorithm improves the channel usage of short-term flows with nodes that are multiple hops from the gateway by a factor of 7 in some cases with a penalty of 20% reduction in total throughput across all nodes. Our proposed algorithm also has a better performance than two other schemes in terms of a higher fairness index.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".