SRL-Enabled QoS model for mobile ad hoc networks
Bibliographic record
Abstract
Due to the dynamic network topology and bandwidth constraints of Mobile Ad hoc NETworks (MANETs), existing quality of service (QoS) models for wired networks, i.e. Integrated Service (InteServ) and Differentiated Service (DiffServ) are not applicable on MANETs. In this paper, we propose the SRL-Enabled QoS Model (SEQM) for MANETs by extending a QoS routing protocol: Supernode-based Reverse Labeling (SRL) algorithm, which considers QoS provisioning, specifically bandwidth and delay together. SRL utilizes a hierarchical structure to improve performance and enhance QoS routing. Besides extending SRL with on-demand service proxy, SEQM also includes dynamic traffic negotiation and resource provisioning. Preliminary simulation results show that SEQM performs effectively in terms of throughput and end-to-end delay.
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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 | 0.000 |
| Open science | 0.001 | 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".