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Record W1809963723

Online data migration for autonomic provisioning of databases in dynamic content web servers

2005· article· en· W1809963723 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

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2005
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceServerBenchmark (surveying)ProvisioningDatabaseTransaction processingDistributed computingDatabase transactionReplication (statistics)Computer network
DOInot available

Abstract

fetched live from OpenAlex

This paper introduces an efficient data migration technique for provisioning new databases to workloads in dynamic content servers. Although many solutions for database replication exist, an efficient method for joining new replicas to a running system has not been implemented. We propose and implement a data migration algorithm that allows quick addition of replicas with minimal disruption of transaction processing. Furthermore, we show that our approach can also be used for fault management and re-integrating failed databases. We investigate our algorithm for transparent provisioning in the database tier using the TPC-W e-commerce benchmark and the RUBIS online auction benchmark. We demonstrate that our technique provides quality of service under different load and failure scenarios.

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)0.002
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: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.272
GPT teacher head0.447
Teacher spread0.175 · 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