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Record W2135273046 · doi:10.1145/1272366.1272375

Cooperative secondary authorization recycling

2007· article· en· W2135273046 on OpenAlexaff
Qiang Wei, Matei Ripeanu, Konstantin Beznosov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCaching and Content Delivery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceAuthorizationScalabilityCacheServerSoftware deploymentComputer networkDistributed computingComputer securityDatabaseOperating system

Abstract

fetched live from OpenAlex

As distributed applications such as Grid and enterprise systems scale up and become increasingly complex, their authorization infrastructures-based predominantly on the request-response paradigm-are facing challenges in terms of fragility and poor scalability. We propose an approach where each application server caches previously received authorizations at its secondary decision point and shares them with other application servers to mask authorization server failures and network delays.This paper presents the design of our cooperative secondary authorization recycling system and its evaluation using simulation and prototype implementation. The results demonstrate that our approach improves the availability of authorization infrastructures while preserving their performance characteristics. Specifically, by sharing authorizations, the cache hit rate.an indirect metric of availability.can reach 70%, even when only 10% of authorizations are cached. Depending on the deployment scenario, the performance in terms of the average time for authorizing an application request can be reduced by up to 30%.

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)0.004
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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