A new model for evaluating performability under the effects of software aging and rejuvenation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When a fault-tolerant layered distributed system continues its operation despite the presence of component failures, its performance is usually degraded. Its performance can also be degraded if it is executing continuously for a long period of time due to a phenomenon known as Software Aging. To prevent unexpected or unplanned outages due to aging, a pro-active technique called software rejuvenation can be employed. This technique involves gracefully terminating an application and immediately restarting it with a refreshed internal state. For proper modeling of these systems, their performance and dependability characteristics need to be considered in a unified way, called performability. This paper proposes a model to evaluate the effects of software aging and rejuvenation on performability of these layered systems. Specifically a Layered Queueing Network (LQN) is used for performance analysis and a Multi State Fault Tree (MSFT) is used for dependability analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 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 it