Cross‐layer enhancement of TCP split‐connections over satellites links
Bibliographic record
Abstract
Abstract Satellites have played an important role in global telecommunications. However, transmission control protocol (TCP) suffers performance degradations over satellite links due to the long propagation delay and high bit‐error rate. Among methods proposed to alleviate the impact of satellite link characteristics on TCP performance, split TCP connections separated by performance enhancement proxies (PEPs) have been proven attractive because they can keep TCP configurations in the end systems unchanged. While many protocols applied over satellite links between PEPs can effectively mitigate the effect of high loss rates, the long latency still limits the effectiveness of congestion control in these protocols. To minimize the effect of congestion we propose to take advantage of active queue management at the medium access control layer to provide immediate cross‐layer feedback to the TCP segment over satellite. This approach also achieves proper differentiation between packet losses due to channel errors and congestion. Simulation results show that our novel mechanism can give substantial improvements in TCP performance over satellite networks, compared to the best performing version of TCP with or without PEPs. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 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".