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Record W1993274576 · doi:10.1002/dac.496

A simple, scalable and provably stable explicit rate computation scheme for flow control in communication networks

2001· article· en· W1993274576 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Communication Systems · 2001
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer scienceScalabilityComputationController (irrigation)Simple (philosophy)Flow control (data)Process (computing)Scheme (mathematics)Control (management)AlgorithmControl theory (sociology)Computer networkMathematics

Abstract

fetched live from OpenAlex

Abstract This paper describes fast rate computation (FASTRAC), an explicit rate flow control algorithm for available bit rate (ABR) traffic. Using digital control theory, we develop a simple rate controller for the ABR flow control process. We prove that the controller is stable, fair to all participating sources and configurable with respect to responsiveness. The analysis presented shows that stability of the flow control process depends primarily on two factors, the control update rate and the feedback delay. The implementation of the proposed algorithm is much simpler than other fair rate allocation algorithms. The proposed algorithm demonstrates the ability to scale with speed, distance, different feedback delays, number of users, and number of nodes while remaining robust, efficient, and fair under stressing and dynamic traffic conditions. Copyright © 2001 John Wiley & Sons, Ltd.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.969
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.272
Teacher spread0.255 · 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