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Record W2120835481 · doi:10.1109/wcnc.2006.1683510

Saturation throughput of IEEE 802.11e EDCA based on mean value analysis

2006· article· en· W2120835481 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceDistributed coordination functionIEEE 802.11IEEE 802Quality of serviceThroughputComputer networkIEEE 802.11e-2005Channel (broadcasting)Frame (networking)Real-time computingWirelessWireless networkTelecommunications

Abstract

fetched live from OpenAlex

The IEEE 802.11-based wireless LANs have been widely deployed for local area high-speed data access. The IEEE 802.11e amendment aims at providing QoS provisioning to support real-time multimedia traffic in WLANs. The enhanced distributed channel access (EDCA) is a QoS extension of the distributed coordination function (DCF) in IEEE 802.11a/b/g. In this paper, we propose an analytical model to evaluate the saturation throughput of the IEEE 802.11e EDCA. Our analytical model is based on the use of mean value analysis. We carry out extensive simulation study to validate the accuracy of the proposed model. Our scheme models accurately the effects of the change of contention window size and AIFS (arbitration inter-frame space). Our analytical model is applicable to real-time system tuning and on-line admission control algorithms which require a low computation complexity

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.349

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 communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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

Quick stats

Citations55
Published2006
Admission routes1
Has abstractyes

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