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Record W2114133384 · doi:10.1109/tce.2007.381704

Message Replication and Consumer Database Synchronization Algorithms and System for Highly Available High Performance Intelligent Networks

2007· article· en· W2114133384 on OpenAlexaff
Parthasarathy Guturu, Jatinder Pal, Thomas Heaven, W. K. Jordan, Zhengya Zhu

Bibliographic record

VenueIEEE Transactions on Consumer Electronics · 2007
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer scienceReplication (statistics)Asynchronous communicationDistributed computingHigh availabilitySynchronization (alternating current)Distributed databaseFault toleranceService (business)Data synchronizationComputer networkWireless sensor network

Abstract

fetched live from OpenAlex

For maximizing consumer satisfaction, intelligent network services such as the prepaid card service need to be built upon mechanisms that provide efficiency along with high availability. With multiple replicated service control point (SCP) databases in each one of a number of LAN sites interconnected by WANs for ease of information access and catastrophe tolerance, the proposed distributed software system employs a highly efficacious and innovative fault-tolerant algorithm for replication of messages originating at an SCP to all the others, and a novel asynchronous algorithm to achieve continual synchronization of all the databases with the help of the replicated messages received at different destinations.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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
Published2007
Admission routes1
Has abstractyes

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