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Record W1529876087 · doi:10.1109/mwscas.2003.1562317

IEEE 802.11 Wireless Protocol: User Performance Using Discrete-Time Markov Chains

2006· article· en· W1529876087 on OpenAlexaff
Fayez Gebali

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceMarkov chainComputer networkReservationDistributed coordination functionNetwork allocation vectorMarkov processIEEE 802.15Protocol (science)Discrete time and continuous timeIEEE 802.11Carrier sense multiple access with collision avoidanceInter-Access Point ProtocolMarkov modelIEEE 802.11b-1999WirelessThroughputWireless networkWireless sensor networkWi-FiMathematicsTelecommunications

Abstract

fetched live from OpenAlex

We present discrete-time Markov chain models for users under p-persistent CSMA-CA, and IEEE 802.11g protocols. Numerical simulations of the protocols are presented and indicate that the IEEE 802.11 g has superior performance compared to CSMA-CA systems. The reason for that is the use of reservation slots which reduces the chance of collisions compared.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.258
Teacher spread0.245 · 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.

Study designSimulation or modeling
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

Citations4
Published2006
Admission routes1
Has abstractyes

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