Bibliographic record
Abstract
A common 'finite-burst' mode of wireless links scheduling in CDMA2000 has been shown to cause occupancy oscillations at the bottleneck shared-queue resulting with large overflow-based closely clustered bursts of data-packets drops. The CDMA2000 gateway (PDSN) node is constructed with superior service-rate compared to its downstream core node (PCF). The rate mismatch further allows for traffic load variations and subsequent congestion at the core node. The use of a Xoff/Xon feedback flow control in CDMA2000 was proposed at the 3GPP2. We evaluate the 3GPP2 backpressure proposal for protecting the bottleneck queue during heavy congestion conditions. We devise an adaptive-Xoff/Xon for tandem queues, which extends the traditional Xoff/Xon to provide threshold adaptation according to overflow prediction. The adaptive-Xoff/Xon complements the RED AQM at the bottleneck node, creating a hybrid flow-control model for tandem nodes. Experimental results show that the hybrid flow-control model eliminates packet discards due to overflow at the bottleneck queue, improves throughput, and lowers the overall data packets drop volume. Packets show to not experience backpressure-based delay variation while traversing the tandem queues. An associated cost is low volume of feedback control packets. Larger tandem-queues' average-delays are observed, which result with lower power-function. Hence, degraded combined performances are delivered by the 3GPP2 proposal for backpressure.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".