Streaming Erasure Codes over Multicast Relayed Networks
Bibliographic record
Abstract
This paper studies streaming erasure codes in a relayed multicast setting, where a source wishes to transmit a sequence of messages to two different destinations through a common relay. Our construction extends previously proposed works on the single-destination setting studied in Fong et al. and Facenda et al. to the multicast setting, where each destination can recover the source packets with a correspondingly different delay. A key property of our construction is that it does not require prior knowledge of the maximum number of erasures on the relay-destination link. Instead, it enables the recovery of the source stream with a decoding delay that depends on the number of erasures on the relay-destination links. We demonstrate that if some divisibility conditions are satisfied, then the proposed construction can simultaneously achieve the single-destination delay in Fong et al. for both receivers. Finally we also explain how our proposed construction can be applied in the setting of a single destination when the maximum number of erasures on the relay-destination link is not known beforehand.
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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 | 0.005 |
| 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 | 0.002 |
| 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".