A Method for Satisfying Asynchronous and Periodic Timing Requirements in Real-Time Embedded Systems
Bibliographic record
Abstract
A method for satisfying asynchronous and periodic timing requirements in real-time embedded systems is presented. A guiding principle for this method is that it should exploit to a maximum extent any knowledge about system processes' characteristics that is available both before run-time and during run-time. The method consists of two phases: a pre-run-time phase and a run-time phase. In the pre-run-time phase, some of the asynchronous processes will be converted into new periodic processes while processor capacity will be reserved for all the remaining asynchronous processes. With the use of an optimal scheduling algorithm, the schedulability of the set of the new and original periodic processes will be determined, while the schedulability of all the asynchronous processes will be verified by checking their worst-case response times. In the run-time phase, asynchronous processes are scheduled for execution while guaranteeing that all the processes that have already been scheduled in the pre-run-time phase will always meet their deadlines.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".