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Record W1696850826 · doi:10.1109/nca.2004.1347804

Towards a quality of service aware public computing utility

2004· article· en· W1696850826 on OpenAlexaff
Muthucumaru Maheswaran, Balasubramaneyam Maniymaran, Shah Asaduzzaman, Aritra Mitra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceGrid computingQuality of serviceOverlayUtility computingResource (disambiguation)Service (business)Overlay networkArchitectureGridConstruct (python library)Quality (philosophy)Service qualityScheme (mathematics)Peer-to-peerDistributed computingComputer networkWorld Wide WebThe InternetCloud computingBusinessOperating system

Abstract

fetched live from OpenAlex

This work describes a design for a quality of service aware public computing utility (PCU). The goal of the PCU is to utilize the idle capacity of the shared public resources and augment the capacity with dedicated resources as necessary, to provide high quality of service to the clients at the least cost. Our PCU design combines peer-to-peer (P2P) and grid computing ideas in a novel manner to construct a utility-based computing environment. In This work, we present the overall architecture and describe two major components: a P2P overlay substrate for connecting the resources in a global network and a community-based decentralized resource management system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.084
GPT teacher head0.317
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2004
Admission routes1
Has abstractyes

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