Prioritized retransmission in slotted all-optical packet-switched networks
Bibliographic record
Abstract
Feature Issue on Photonics in SwitchingWe consider an all-optical slotted packet-switched network interconnected by a number of bufferless all-optical switches with contention-based operation. One approach to reduce the cost of the expensive contention resolution hardware could be retransmission in which each ingress switch keeps a copy of the transmitted traffic in the electronic buffer and retransmits whenever required. The conventional retransmission technique may need a higher number of retransmissions until traffic passes through the network. This in turn may lead to a retransmission at a higher layer and reduce the network throughput. In this paper, we propose and analyze a simple but effective prioritized retransmission technique in which dropped traffic is prioritized when retransmitted from ingress switches so that the core switch can process them with a higher priority. We present the analysis of both techniques in multifiber network architecture and verify it via simulation to demonstrate that our proposed algorithm can limit the number of retransmissions significantly and can improve TCP throughput better than the conventional retransmission technique.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".