Modeling BitTorrent-Based P2P Video Streaming Systems in the Presence of NAT Devices
Bibliographic record
Abstract
BitTorrent has been a very successful peer-to-peer (P2P) file-sharing application, and several BitTorrent-based P2P video streaming systems have been proposed in the literature. Nowadays, network address translation (NAT) has been widely used since it reduces the usage of IP addresses, but it is also considered as a factor that degrades the performance of P2P systems because NAT limits the direction of connectivity. In order to understand what impact NAT has on the performance of BitTorrent-based P2P video streaming systems, we build an analytical model which can be used to predict the average continuity index, a video streaming performance metric, when a fraction of the participating peers are behind NAT devices. A software simulator is written to validate our analytical model, and the simulation results also give some insights on the fairness issue of P2P video streaming systems in the presence of NAT devices. In this paper, both our analytical model and simulation results are presented and verified.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".