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Record W2138816454 · doi:10.1109/mascot.2008.4770565

TCP over WiMAX: A Measurement Study

2008· article· en· W2138816454 on OpenAlexaff
Emir Halepovic, Qian Wu, Carey Williamson, Majid Ghaderi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer networkComputer scienceTCP Westwood plusZeta-TCPWiMAXTCP global synchronizationTCP accelerationThroughputTCP Friendly Rate ControlTCP VegasTransmission Control ProtocolWirelessNetwork packetTelecommunications

Abstract

fetched live from OpenAlex

We present active measurement results from a commercial IEEE 802.16/WiMAX-based network, with primary focus on TCP performance. We compare four TCP variants, namely New Reno, Cubic, Vegas and Veno, using throughput, round-trip time (RTT), and retransmission rate metrics. While all TCP variants achieve similar throughput, they do so in different ways, with different impacts on the network performance. We identify adverse effects of TCP window auto-tuning in this environment and demonstrate that on the downlink, congestion losses dominate wireless transmission errors. We reveal several issues for this WiMAX-based network, including limited bandwidth for TCP, high RTT and jitter, and unfairness during bidirectional transfers. Such a network environment may be challenging for many wireless Internet applications, such as remote login, VoIP, and video streaming.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.040
GPT teacher head0.223
Teacher spread0.182 · 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 designObservational
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

Citations38
Published2008
Admission routes1
Has abstractyes

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