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Record W2114058452 · doi:10.1109/lcn.2000.891078

The performance of TCP over ATM on lossy ADSL networks

2002· article· en· W2114058452 on OpenAlexafffund
Guang Lu, Rob Simmonds, Brian Unger, Carey Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
FundersH2020 European Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsCUBIC TCPTCP global synchronizationComputer scienceAsymmetric digital subscriber lineComputer networkTCP accelerationTCP Friendly Rate ControlTCP tuningTransmission Control ProtocolZeta-TCPTCP delayed acknowledgmentPacket lossDigital subscriber lineReal-time computingNetwork packet

Abstract

fetched live from OpenAlex

This paper studies the performance of the transmission control protocol (TCP) over asynchronous transfer mode (ATM) when asymmetric digital subscriber line (ADSL) technology is used in the local loop. TCP can experience performance degradation in this network architecture because of protocol conversion overhead and data losses due to transmission errors. A simulation model is developed to simulate ADSL network components and noisy local loops. The simulation experiments are designed to study the impact of channel errors on TCP performance for unidirectional bulk data transfers, using both an independent error model and a burst error model. The primary performance metrics are cell loss ratio, packet loss ratio, and TCP effective throughput. The simulation results illustrate how TCP is affected by channel errors, as well as the impacts of the TCP maximum segment size (MSS), switch buffer size, bandwidth asymmetry, and the percentage of noisy lines.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.209

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 science0.0010.000
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 head0.008
GPT teacher head0.187
Teacher spread0.178 · 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 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

Citations4
Published2002
Admission routes2
Has abstractyes

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