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Record W1786376018 · doi:10.1109/pacrim.1997.620403

Preemptive reservation arbitrated access for transporting variable bit rate isochronous traffic over dual bus metropolitan area networks

2002· article· en· W1786376018 on OpenAlexaff
Henry C. B. Chan, Victor C. M. Leung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer networkReservationComputer scienceChannel access methodDistributed-queue dual-busAccess controlStatistical time division multiplexingQueueAccess networkMetropolitan area networkMultiplexingAsynchronous Transfer ModeTelecommunicationsLocal area networkWireless

Abstract

fetched live from OpenAlex

This paper proposes and analyzes a preemptive reservation arbitrated access scheme to facilitate the transport of real time traffic over dual bus metropolitan area networks (MANs) on a bandwidth on demand basis. This access protocol allows full statistical multiplexing among variable bit rate isochronous (VBRI) traffic while providing nearly isochronous transport service thus enabling significant capacity improvement compared to pre-arbitrated (PA) access. We have analyzed its performance by simulations validated by idealized analytical results. Results indicate that at the expense of requiring one more control bit in the access control field (ACF), preemptive RA access provides much fairer service than the 1-persistent RA access scheme. It is also not too sensitive to propagation delay unless the delay is unrealistically high. In general, RA access offers a valuable complement to the existing PA and queue-arbitrated (QA) access methods to provide a complete set of transport solutions for all B-ISDN services.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.255
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

Citations0
Published2002
Admission routes1
Has abstractyes

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