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Record W1529277239 · doi:10.1109/glocom.2004.1378201

Self-tuning PI TCP flow controller for AQM routers with interval gain and phase margin assignment

2005· article· en· W1529277239 on OpenAlex
Yang Hong, Ou Yang, Changcheng Huang

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsCarleton UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsActive queue managementControl theory (sociology)Phase marginPID controllerRobustness (evolution)Network congestionQueueComputer scienceController (irrigation)Transmission Control ProtocolReal-time computingComputer networkEngineeringAmplifierControl engineeringBandwidth (computing)Network packetControl (management)Operational amplifier

Abstract

fetched live from OpenAlex

We propose a self-tuning proportional-integral (PI) controller for active queue management (AQM) in the Internet. Classical control theory is applied in the controller design. We assign a proper interval of gain and phase margins to achieve good AQM performance while adapting the AQM control system to great traffic load changes very well. Based on the knowledge of the queue size, our PI controller can regulate the TCP source window size to clamp the steady value of queue size to specified target buffer occupancy. OPNET simulations demonstrate that, with our self-tuning PI controller applied, the network shows good stability robustness.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Quick stats

Citations33
Published2005
Admission routes2
Has abstractyes

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