Bibliographic record
Abstract
The environmental impact of Information and Communication Technologies (ICT) continues to grow, driven notably by increasing usage, rebound effects, and emerging demands. However, despite the virtual nature of its services, the sector remains inherently constrained by its materiality and cannot rely on an infinite pool of resources. As a result, the wide variety of supported services may need to be managed under stricter limits within hosting facilities in the future. Contrary to common assumptions, we show that tenants typically do not share computing resources, even in environments commonly perceived as mutualized, such as cloud platforms. Time-sharing has been progressively phased out for reasons of performance, security, predictability, and, perhaps more importantly, due to the decreasing cost of computing resources. This paper advocates for managing fewer physical resources by improving resource sharing between tenants. It represents a paradigm shift, moving beyond traditional time-sharing at the hardware level to a higher abstraction. This approach entails "doing with fewer resources" under conditions of "reduced performance". Nonetheless, enhancing the mutualization of infrastructure can reduce cluster sizes (through consolidation) and improve energy efficiency, with gains related to the accepted performance trade-off, a situation potentially more socially acceptable than eliminating services. We review the current state of the art, identify challenges and opportunities, propose interpretations of Time-Shared Computing, and outline key research directions.
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.
How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".