Resource and connection admission control in real-time transport protocols with deterministic QoS guarantees
Bibliographic record
Abstract
Real-time multimedia applications will require guaranteed quality of service (QoS) such as a bound on the maximum message delay and/or on the maximum message loss rate. This poses an exciting challenge to the highspeed transport protocol design and implementations. In this paper, we study the resource and connection admission control algorithms, and give the necessary and sufficient conditions for the schedulability, of n real-time transport connections at a destination host under preemptive and non-preemptive deadline scheduling policy for deterministic QoS guarantees. These necessary and sufficient conditions form the mathematical basis for the deterministic QoS guarantees in real-time transport communication services. On the basis of these necessary and sufficient conditions, we give the connection admission control algorithms for deterministic QoS guarantees. We also calculate the buffer space needed for each real-time transport connection. The results show that real-time transport connections with deterministic QoS guarantees can reserve the buffer space at the establishment phase, and no flow control mechanism is required during the data transport phase. Our results could be applied to other fields as well, such as real-time operating systems.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".