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Record W2126588260 · doi:10.1109/glocom.1989.63958

A distributed queue metropolitan area network for combined video, voice, wideband data and narrowband data

2003· article· en· W2126588260 on OpenAlexaff
Michel Kadoch, A.K. Elhakeem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer networkComputer scienceNarrowbandNetwork packetWidebandFrame (networking)Priority queueQueueing theoryQueueProtocol (science)Distributed computingReal-time computingTelecommunicationsEngineeringElectronic engineering

Abstract

fetched live from OpenAlex

The authors examine a distributed queue metropolitan area network that serves video, voice, and wideband and narrowband data traffic. The protocol that is required for such combined services in the QPSX (queue packet and synchronous circuit exchange) network is proposed, and the performance of this protocol is computed. An integration scheme of the movable frame type is proposed to guarantee different types of services, a basic capacity plus a capacity on the demand. In light of the proposed protocol, the flexibility of the QPSX network was realized. The mathematical model of the proposed system is formulated, and the computation of the performance of a network example is derived. The results show the high capacity potential of such a network. It was found that the best priority scheme is the so-called restricted priority scheme.>

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.265
Teacher spread0.227 · 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

Citations2
Published2003
Admission routes1
Has abstractyes

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