Task Execution Availability Prediction in the Enterprise Desktop Grid
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
Desktop grid uses an idle cycle of desktop PC’s in Intranet and Internet environments for large-scale computation. Heterogeneity and volatility of hosts within this environment are lead to consider issues of availability of resources. Resource availability is critical for the reliability and responsiveness of services. In this paper, two prediction systems have been introduced for task execution availability of resources in the enterprise desktop grid platform. The first one is based on cellular automata and the other one according to Bayesian network. The accuracy of proposed prediction systems is evaluated via four real desktop grids. In spite of highly volatile environment, the meaningful and robust prediction results have been gained. A comparison between two prediction systems indicates that cellular automata have a better behaviour than Bayesian network. It can predict the behaviour of resources in the desktop grid with the prediction accuracy of %95.5.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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