Real-time transport for assured forwarding: an architecture for both unicast and multicast applications
Bibliographic record
Abstract
This paper presents a summary of our work on developing an architecture for transporting real-time traffic (MPEG4 video in this paper) in IP networks that provide service differentiation. We target our architecture at assured forwarding (AF) style services. This architecture assumes loss differentiation in the network and the network's ability to provide ECN messages to the sender. We did not consider policing/shaping at the edge routers. Rather we considered a more general case where marking and flow control are provided at the senders. For this network model, we developed a rate adaptation algorithm that can operate in both unicast and multicast applications with a minor modification. The simulation results presented in this paper represent the multicast case. The results show how the rate adaptation algorithm accommodates different receivers with different networking capabilities and provides them with different qualities by taking advantage of the queue management capabilities of the AF service. We also show the results of testing this architecture with different AF queuing mechanisms, namely RIO and WRED.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".