The effects of adaptive error correcting schemes on satellite optimized TCP
Bibliographic record
Abstract
With the popularity of satellite networks as a means for Internet delivery, the performance of the Transmission Control Protocol (TCP) over satellite links has been well studied.Unfortunately, the protocol has shown problems with channel utilization in such environments, which is a key performance factor for satellite operators.Performance enhancing proxies are one solution to this problem, and have been shown to provide significant improvements in channel utilization.Recent research, however, has been focused on the use of adaptive error correction in satellite networks at the lower layers, resulting in the ratification of the DVB-S2 standa¡d.While adaptive error correction can improve channel utilization when channel conditions are good, it also results in decreases in available user bitrate during noisy periods due to the addition of parity bits.The research performed in this thesis shows that the throughput of a performance enhancing proxy suffers when adaptive error correction is introduced, resulting in up to 20Vo of the bandwidth being wasted during poor channel conditions.A solution involving the addition of a simple bandwidth estimation scheme to the proxy is studied, and is successful in increasing the average channel utilization in poor conditions to almost 90Vo.Alternatively, it is shown that the introduction of a secondary TCP flow running in parallel with the performance enhancing proxy traffic can result in neat lÙOVo channel utilization when priority queues are introduced at the satellite gateway.Tightly integrating performance enhancing proxies with the satellite gateways that employ adaptive effor correction is recommended as the best solution.-tr-AcTNowLEDcEMENTS Many thanks to my family for their patience and support during my thesis, in particular to
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".