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Record W2383432666

Fault-tolerance Storage Scheme Based on RS Code

2010· article· en· W2383432666 on OpenAlexaff
Yang Xiao-yuan

Bibliographic record

VenueJisuanji gongcheng · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsThe Alberta Paraplegic Foundation
Fundersnot available
KeywordsComputer scienceFault toleranceScheme (mathematics)Computer data storageReliability (semiconductor)Construct (python library)Reliability engineeringCode (set theory)Distributed data storeFault (geology)Embedded systemStorage efficiencyDistributed computingDatabaseComputer hardwareComputer network
DOInot available

Abstract

fetched live from OpenAlex

When a distributed storage system stores data,if there are failures of one or several devices,not only the data in the device can not be used,but also the user is unable to visit the resources completely.Aiming at this problem,this paper proposes a fault-tolerance storage scheme based on Reed-Solomon(RS) code,which can restore the faults and realize fault-tolerant when the number of false devices does not exceed m.The scheme has high security and executive efficiency.It can satisfy the requirements of fault-tolerant in storage systems and can be used to construct storage systems which have high reliability requirements.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.270
Teacher spread0.254 · 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.

Study designSimulation or modeling
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

Citations0
Published2010
Admission routes1
Has abstractyes

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