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Record W2139894977 · doi:10.1109/ccece.1999.807191

Simulation of the model of computer mirroring based on difference queues

2003· article· en· W2139894977 on OpenAlexaff
H.J. Teh, Przemyslaw Pocheć

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMirroringComputer scienceBackupQueueQueue management systemFork–join queueParallel computingReal-time computingComputer networkOperating system

Abstract

fetched live from OpenAlex

The paper describes modelling of the operation of a special case of two computer systems operating in parallel: computer mirroring. In computer mirroring one of the systems is identified as the main and the other as the backup computer, and both computers execute the same tasks. Each system operates independently and is modelled as an execution unit processing a queue of tasks. The mirroring aspect of the system is modelled analytically with a difference queue. The analytical results are then verified by simulating the behaviour of the parallel network of two queues, and measuring the resulting difference queue. The simulation results confirm the modelling of the behaviour of the d-queue as the standard M/M/1 queue. Simulation results are compared against theoretical estimates for number of tasks in the queue, in the system, mean time in the system, in the queue, for the main system, the backup system, and for the d-queue.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.254
Teacher spread0.218 · 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 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

Citations1
Published2003
Admission routes1
Has abstractyes

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