Bandwidth efficient multicast routing in multi-channel multi-radio wireless mesh networks
Bibliographic record
Abstract
Multi-channel multi-radio (MCMR) wireless mesh networking is an emerging technology that enables high-throughput networking capability using multiple channels and multiple radios per mesh router. Traditional multicast routing algorithms such as shortest path trees and minimum Steiner trees do not consider the wireless broadcast advantage or the underlying channel assignments (i.e., channel diversity) in a MCMR wireless mesh network (WMN). In this paper, we propose a multicast routing algorithm for MCMR WMNs that takes into account the wireless broadcast advantage and channel diversity in order to minimize the amount of network bandwidth consumed by the routing tree. The algorithm does so by minimizing the number of transmissions required to deliver one packet from the source to all the destinations of a multicast group. Experimental results show that the proposed algorithm constructs routing trees having the least number of transmissions when compared with traditional trees such as shortest path trees, minimum Steiner trees, and minimum number of forwarders trees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".