An adaptive compression technique based on real-time RTT feedback
Bibliographic record
Abstract
The dynamic nature of traffic over Internet protocol (IP) networks often induce high end-to-end latency and packet loss rate. These problems hamper the Quality of Service (QoS) of various conventional and emerging applications over Internet. In order to mitigate these challenges and improve the network efficiency, an adaptive compression technique (ACT) is proposed. ACT exploits lossless data compression algorithms where compression is applied seamlessly to a packet's payload. Our adaptive compression is based on the situational awareness of a given network derived from gathered network statistical data, such as the varying Round Trip Time (RTT) as well as the packet loss rate during a transmission session. The real-time observation of the varying RTT and packet loss rate triggers the ACT compression when a defined threshold, which is compared to the observed values, is crossed. Using Network Simulator 3 (NS3), two different real-time latency reduction schemes using ACT were compared with an uncompressed transmission. The results show ACT improvement in network conditions such as reducing the number of dropped packets by approximately 30%, as well as, reducing delayed packet transmissions by 26.5% which results in fundamentally increasing the TCP efficiency by approximately 3%.
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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 | 0.001 | 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".