Wireless Profiled TCP Performance over Integrated Wireless LANs and Cellular Networks
Bibliographic record
Abstract
An analytical framework for studying the performance of wireless profiled TCP (WP-TCP) flows over the integrated wireless LAN and cellular networks is proposed. The framework can be used to analyze the short-term performance during vertical handover and long-term performance of WP-TCP for a given set of network and protocol parameters. It captures the WP-TCP behavior under the influence of wireless channel errors, step change in network parameters and excessive packet losses due to vertical handovers. Extensive simulations are conducted to verify the accuracy of the analytical framework. The main findings in this study are: (1) when the network is subjected to hard handovers, increasing the maximum window size improves the efficiency in a high transmission error environment, but degrades the efficiency in a low transmission error environment; (2) increasing the congestion window reduces the chances of premature timeouts during soft upward vertical handover; and (3) depending on duplicate ACK threshold, increasing the congestion window can increase or reduce the chances of false fast retransmit during soft upward vertical handover.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".