Measuring Performance of Web Protocol with Updated Transport Layer Techniques for Faster Web Browsing
Bibliographic record
Abstract
Popular Internet applications such as web browsing, web video download or variable-rate voice suffer from standard Transport Control Protocol (TCP) behaviour because their transmission rate and pattern are different from conventional bulk transfer applications. Previous works have analysed the interaction of these applications with the congestion control algorithms in TCP and proposed Congestion Window Validation (CWV) as a solution. However, this method was incomplete and has been shown to present drawbacks. This paper focuses on the ‘newCWV’ which was proposed to address these drawbacks. newCWV depicts a practical mechanism to estimate the available path capacity and suggests a more appropriate congestion control behaviour. These new modifications benefit variable-rate applications that are bursty in nature, with shorter transfer durations. In this paper, this algorithm was implemented in the Linux TCP/IP stack and tested by experiments, where results indicate that, with newCWV, the browsing can get 50% faster in an uncongested network.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".