Bibliographic record
Abstract
Peer-to-Peer (P2P) Video-on-Demand (VoD) systems with multiple channels are called multi-channel P2P VoD systems, which can be categorized into independent-channel P2P VoD systems and correlated-channel P2P VoD systems. Most of the existing P2P VoD systems are independent-channel P2P systems, in which the peers share resources with each other within the same channel. In this paper, we examine the cross-channel resource sharing in correlated-channel P2P VoD systems. We optimize the server upload allocations among channels to maximize the average streaming capacity. Furthermore, we introduce bandwidth amplifiers to establish cross-channel links, thus enabling cross-channel sharing of peer upload bandwidths. We demonstrate in the simulations that the correlated-channel P2P VoD systems with cross-channel resource sharing can achieve a higher average streaming capacity compared to the independent-channel P2P VoD systems without cross-channel resource sharing.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".