Loss recovery at the ATM layer for latency-constrained reliable multicast
Bibliographic record
Abstract
Many multicast applications have stringent time constraints, and require a data delivery guarantee. A cell discarded by a switch causes the loss of the entire packet, and eventually requires the whole packet to be retransmitted. In the case of multicast, many copies of the same packet are often retransmitted unnecessarily, reaching receivers which did not request the packet. This problem is called the exposure problem. Recovery latency would be lower if only the lost data were retransmitted and not the entire packet. To reduce unnecessary data retransmission, and thus recovery latency, we propose a reliable multicast protocol in which detection of data loss and retransmission are performed at the ATM layer instead of at the transport layer. The unit of recovery is ATM cells, instead of transport-layer packets: only missing cells are retransmitted. The proposed protocol uses the ATM physical tree structure for local recovery. It is thus scalable and offers low recovery latency. The protocol is particularly beneficial to large scale reliable multicast applications with stringent latency requirements, such as distribution of financial data, distance learning and Internet conferencing. We have run experiments to compare the performance of ATM-layer recovery and transport-layer recovery. Simulation results show that, with ATM-layer recovery, the average retransmission delay is significantly lower, and the connection throughput is higher under congestion.
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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 | 0.000 | 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".