A Rate Adaptive Admission Control Protocol for Multimedia Wireless Mesh Networks
Bibliographic record
Abstract
Wireless mesh networks (WMNs) have become immensely popular these days. In order to satisfy user service requirements, multimedia applications need quality of service (QoS) support. Since the mesh routers are usually stationary in WMNs, a better performance is expected in WMNs as compared to ad hoc networks. But sustaining QoS in wireless mesh networks still remains a challenging task. A fundamental management function in WMNs for backing up multimedia applications is to have admission control. In this paper, we propose a protocol called Rate Adaptive Routing on Cliques Admission Control (RA-RCAC) that provides rate adaptive admission control such that the network layer provides feedback in case of network congestion at the application layer. By simulations, RA-RCAC is compared against MARIA [1] and RCAC [2], showing its superiority in terms of throughput, end-to-end delay, packet delivery ratio and loss ratio, chosen as performance metrics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".