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Record W2141202063 · doi:10.1109/jsac.2004.826929

Saturation Throughput Analysis of IEEE 802.11e Enhanced Distributed Coordination Function

2004· article· en· W2141202063 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

VenueIEEE Journal on Selected Areas in Communications · 2004
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceDistributed coordination functionThroughputQuality of serviceComputer networkAccess controlIEEE 802Bandwidth (computing)Wireless Multimedia ExtensionsIEEE 802.11e-2005Distributed computingWirelessIEEE 802.11Wireless networkTelecommunications

Abstract

fetched live from OpenAlex

The IEEE 802.11 Task Group E will soon approve the 802.11e standard for medium access control (MAC) layer quality-of-service (QoS) enhancements to the 802.11 protocol, and it is widely believed that these enhancements will allow 802.11 technology to form the foundation of high-bandwidth vertically integrated networks. At the heart of 802.11e is a modified contention-based access mechanism, named the enhanced distributed coordination function (EDCF). In this paper, we propose and validate an analytical model for the saturation throughput of EDCF. Key to the accuracy of our model is a treatment of the postcollision period, which has been ignored by all previous 802.11 models. With results from the ns-2 simulator, we show that our model can accurately predict throughput over a wide range of scenarios, and thereby demonstrate its usefulness as a predictive tool for use in QoS provision. With context provided by our analytical model, we discuss the primary throughput differentiation mechanisms of EDCF.

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)0.001
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 score0.935
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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