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Record W2084692902 · doi:10.4310/cis.2003.v3.n4.a4

A Performance Analysis of the 802.11 Wireless Lan Medium Access Control

2003· article· en· W2084692902 on OpenAlexfundno aff
Nitin Gupta, P. R. Kuman

Bibliographic record

VenueCommunications in Information and Systems · 2003
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchFederation for the Humanities and Social SciencesDeutscher Akademischer AustauschdienstNational Science Foundation
KeywordsWireless lanComputer networkComputer scienceAccess controlIEEE 802.11e-2005Wireless distribution systemWirelessWireless networkTelecommunicationsWi-Fi array

Abstract

fetched live from OpenAlex

We study the performance of the IEEE 802.11 protocol. We present an extension of a methodology for the collocated one-hop case which allows the incorporation of channel errors. The results closely agree with simulation results. A delay analysis is also presented. We also present an extension of this methodology to the multi-hop case with non-collocated nodes. The approach uses specific topology dependent relations. Specific results are presented for the ring and mesh topologies, and compared against simulation results. 1. Introduction. Wireless networking technologies are increasingly becoming widespread. Various wireless communication standards have evolved which try to provide protocols and standards for medium access control in the shared wireless medium. The IEEE 802.11 protocol[3], Bluetooth[7], HomeRF[9] (now disbanded) and the HiperLAN[8] are examples of such standards. The IEEE 802.11 protocol is the most widely used.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.297
Teacher spread0.261 · 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 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

Citations93
Published2003
Admission routes1
Has abstractyes

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