<title>On meeting P2P streaming bandwidth demand with limited supplies</title>
Why this work is in the frame
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Bibliographic record
Abstract
As a basic requirement of live peer-to-peer multimedia streaming sessions, the streaming playback rate needs to be strictly enforced at each of the peers. In real-world peer-to-peer streaming sessions with very large scales, the number of streaming servers for each session may not be easily increased, leading to a limited supply of bandwidth. To scale to a large number of peers, one prefers to regulate the bandwidth usage on each of the overlay links in an optimal fashion, such that limited supplies of bandwidth may be maximally utilized. In this paper, we propose a decentralized bandwidth allocation algorithm that can be practically implemented in peer-to-peer streaming sessions. Given a mesh P2P topology, our algorithm explicitly reorganizes the bandwidth of data transmission on each overlay link, such that the streaming bandwidth demand is always guaranteed to be met at any peer in the session, without depending on any <i>a priori</i> knowledge of available peer upload or overlay link bandwidth. Our algorithm is especially useful when there exists no or little surplus bandwidth supply from servers or other peers. It adapts well to time-varying availability of bandwidth, and guarantees bandwidth supply for the existing peers during volatile peer dynamics. We demonstrate the effectiveness of our algorithm with in-depth simulation studies.
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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 it