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Record W1834079802 · doi:10.1109/ipccc.2002.995179

Fast backward congestion notification mechanism for TCP congestion control

2003· article· en· W1834079802 on OpenAlexaff
Fei Peng, 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 networkComputer scienceTCP Friendly Rate ControlTCP global synchronizationTCP accelerationTCP tuningNetwork congestionCUBIC TCPTCP Westwood plusExplicit Congestion NotificationZeta-TCPTransmission Control ProtocolThroughputNode (physics)TCP delayed acknowledgmentNetwork packetWirelessTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

The novel mechanism proposed uses a simple implementation to inform the traffic source at a very early stage that the network is becoming overloaded or congested and ask the source to slow down its transmission rate. Since TCP uses acknowledgments (ACKs) to adjust the number of packets sent over the network, the basic idea of our scheme is to control (or delay) TCP ACKs in the access node where its forward connection through the network is congested. To shorten the control loop, the congested network node generates ICMP (Internet control message protocol) source quench to initiate ACK control at the access node at the onset of congestion. By theoretical analysis and simulations, the mechanism is proven to be very effective in improving TCP throughput and fairness performance and reducing buffer occupancy. In particular, formulae for buffer occupancy and average throughput are derived relative to the distance between the congested node and the source terminal. It is important to note that TCP behavior does not have to be amended in any way.

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 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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations3
Published2003
Admission routes1
Has abstractyes

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