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Record W2121705942 · doi:10.1109/e-science.2007.37

G-FRoM: Grid Resources Pricing A Fuzzy Real Option Model

2007· article· en· W2121705942 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGridComputer scienceGrid computingFuzzy logicDistributed computingQuality of servicePerspective (graphical)Quality (philosophy)Operations researchArtificial intelligenceComputer networkEngineering

Abstract

fetched live from OpenAlex

Current research efforts in grid computing show that the available grid resources exist as non-storable compute cycles (grid compute commodities) and distributed geographically across dissimilar organizations with diverse resources usage polices. Therefore, guaranteeing grid resources availability as well as pricing them raises a number of challenging issues in several areas of computer applications. To guarantee QoS we propose a price-based, quality-aware model. We design and develop our model using the financial option theory from a real option perspective and value the grid resources by treating them as real assets. Our hybridized model combines both advantages of fuzzy logic reasoning and real options of a decision-based system. We have taken into account the fact that the grid resources availability depend on the time of use and are transient, and hence solutions from our model captures the realistic value of the grid resources and guarantees the certainty in the resources availability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.257
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it