A novel application of option pricing to distributed resources management
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
In this paper, we address a novel application of financial option pricing theory to the management of distributed computing resources. To achieve the set objective, first, we highlight the importance of finance models for the given problem and explain how option theory fits well to price the distributed grid compute resources. Second, we design and develop a pricing model and generate pricing results based on the trace data drawn from two real grids: one commercial grid Auvergrid and one experimental platform grid LCG. We evaluate our proposed model using various grid compute resources (such as memory, storage, software, and compute cycles) as individual commodities. By carrying out several experiments, a justification of the pricing model is obtained by comparing real behavior to a simulated system based on the spot price for the resources. We further enhanced our model to achieve a desirable balance between Quality of Service (QoS) and profitability from the perspectives of the users and resource operators respectively.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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