Multipath routing with adaptive playback scheduling for Voice over IP in Service Overlay Networks
Bibliographic record
Abstract
Voice over IP (VoIP) quality of service provision over the best effort Internet remains a challenging task since an interactive level conversation has strict delay, loss and delay jitter requirements. The ITU-T E-model [1] defines R-factor to measure the subjective quality of VoIP phone calls. Multipath routing and adaptive playback scheduling have been proposed to improve the quality of VoIP phone calls. However, it is still not clear how to select a multipath at the sender so that the best quality is achieved for voice signals. We propose a novel mechanism to select the optimal multipath that provides the best R-factor for VoIP phone calls with adaptive playback scheduling being applied at the receiver. We evaluate the VoIP quality for the proposed mechanism by comparing the R-factor of the VoIP calls sent through the optimal multipath with that of the VoIP calls sent through the direct path (the shortest hop path decided by the underlying network). The results show that the proposed method can raise the VoIP quality and provide much more stable quality for VoIP calls.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".