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Record W2098537095 · doi:10.1109/pimrc.2008.4699703

Modeling hidden terminals in IEEE 802.11 networks

2008· article· en· W2098537095 on OpenAlexaff
Özgür Ekici, Abbas Yongaçoğlu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceHidden node problemNode (physics)Computer networkDistributed coordination functionIEEE 802.11sWireless networkWireless ad hoc networkFootprintWirelessIEEE 802.11Distributed computingWireless mesh networkEngineeringTelecommunicationsWi-Fi array

Abstract

fetched live from OpenAlex

Analytic performance of IEEE 802.11 distributed coordination function that takes into account hidden node problem and unsaturated traffic condition is presented for symmetric networks. This enables us to estimate the performance of practical wireless local area networks more accurately. It is shown that the presence of hidden nodes barely affects the network performance in low traffic conditions, but it causes up to 50% performance loss in moderate-to-high traffic scenarios. It is also found that the footprint of the first hidden node had the most decremental effect compared to subsequent hidden nodes. Analytical results presented in the paper are backed by simulation results.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.457

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 head0.042
GPT teacher head0.267
Teacher spread0.226 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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