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Record W2155225845 · doi:10.1109/icc.1997.609936

Performance evaluation of rate-based congestion control schemes for ABR service over broadband satellite networks interworking with ATM/B-ISDNs

2002· article· en· W2155225845 on OpenAlexaff
Bin Zhang, 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 networkNetwork congestionComputer scienceAsynchronous Transfer ModeBroadband Integrated Services Digital NetworkBroadbandBroadband networksIntegrated Services Digital NetworkScheme (mathematics)Default gatewayQuality of serviceReal-time computingTelecommunications

Abstract

fetched live from OpenAlex

This paper evaluates the performance of different rate-based congestion control schemes for ABR services over broadband satellite networks (BSNs) interworking with ATM/B-ISDNs. The explicit forward congestion indication (EFCI) and explicit rate (ER) schemes are considered on their own in single loop end-to-end control, and in combinations in double loop control segmented at the gateway between the two networks. Procedures are formulated to optimize performance in the single loop EFCI scheme. The large buffer requirement at the congested switch in single loop control is effectively reduced by equalizing with the gateway buffer requirement in double loop control, thus facilitating practical interworking. Preliminary results show that in the double loop control scheme best performance is obtained by employing EFCI over the BSN and ER over the B-ISDN.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.026
GPT teacher head0.234
Teacher spread0.208 · 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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