<title>Performance of MPEG-2 video-on-demand over RSVP</title>
Bibliographic record
Abstract
In this paper we propose a framework for the efficient transmission of video traffic through IP-based networks. The IETF's Integrated Services is used to enable the provision of the QoS guarantees required by the video application. Specifically, the Resource ReSerVation Protocol (RSVP) allows the end user to request deterministic QoS guarantees from the network. Since our focus is on pre-recorded video data, the video data is pre-processed through a smoothing operation prior to its transmission. The use of the smoothing algorithm reduces the network resources facilitating the resource reservation process. First, we evaluate the performance of the smoothing algorithm chosen for this study through its sensitivity to processing and network latencies. The second phase of the experimental work consists in evaluating the performance of an RSVP-aware switching point for video transmission supplemented by a smoothing mechanism and a class based queuing scheduler. The overall system evaluation is carried out using various video streams and under different load conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".