Towards TCP optimization in wireless networks by a frame based cross layer routing metric
Bibliographic record
Abstract
With the rapid development of wireless networks, the solution for degradation of Transmission Control Protocol (TCP) over wireless networks becomes more and more significant because of the software reusability. In order to improve the performance of TCP protocol, several studies have been proposed in different directions. Some of them attempt to find a suitable path for TCP transmission. Expected Transmission Count (ETX) is one of the most famous routing metrics to select a path with the least expected transmissions. However, ETX does not consider the Automatic Repeat Request (ARQ) mechanism in TCP, which generates extra transmissions. By modifying the ETX, we proposed a Frame-based TCP-ETX (FTCP-ETX), which calculates the expected frame transmissions for a TCP segment transmission. To evaluate our proposal, we conducted simulations by comparing FTCP-ETX, ETX and DSDV. Simulation results reveal that our routing metric improves TCP performance by selecting a better path.
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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 | 0.001 | 0.001 |
| 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 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".