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Record W1997592258 · doi:10.1109/cts.2012.6261066

On-the-Cloud Computing: Challenges in controlling cloud resources

2012· article· en· W1997592258 on OpenAlexaff
Dan Ionescu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsProvisioningCloud computingComputer scienceVirtual machineUtility computingDistributed computingResource (disambiguation)ImplementationCloud testingCloud computing securityResource management (computing)Resource allocationOperating systemComputer networkSoftware engineering

Abstract

fetched live from OpenAlex

Cloud Computing is defined as a pool of virtualized computer resources deployed and scaled-out quickly through the rapid provisioning of virtual or physical machines. Virtual machine services offered by cloud utility providers led to the creation of the ecosystem of cloud services as they enable customers to use computing resources based on the dynamic behaviour of the application and of the computer resource used. As the control system approach is more and more accepted by the computer research communities the perspective of implementing an adaptive resource provisioning and optimization looked attractive enough for investing efforts and human resources to move it from the theory benches to experimental implementations.

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 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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.001
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 head0.042
GPT teacher head0.245
Teacher spread0.204 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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