Multipriority packet switching on the HYPER switch
Bibliographic record
Abstract
This paper develops an efficient buffer management scheme that makes generic ATM switches capable of supporting delay-sensitive as well as loss-sensitive traffic. The proposed scheme aims at enhancing the performance of ATM switches by maintaining the head cells of output queues in relatively short dedicated output buffers, while maintaining the long tails of overflowing queues in a shared-memory pool where various memory-space management schemes can be applied. Under this scheme, delay-sensitive (high-priority) cells can be forwarded immediately to the output buffers, where priority-based cell scheduling is exercised. Loss-sensitive (low-priority) cells are pushed into the shared-memory only if their output buffers are full. If the shared memory is full, then a suitable push-out scheme must be employed to provide fairness. We investigate the impact of various buffer management and cell scheduling policies on the dynamics of interaction among the two traffic classes. The results demonstrate the effectiveness of the proposed scheme in providing each traffic class with the required quality-of-service (QoS) performance over a wide range of traffic loads and buffer sizes.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".