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Record W1919903260 · doi:10.1109/icc.1999.765528

Data and voice integration in DR-TDMA for wireless ATM networks

2003· article· en· W1919903260 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 Communication Networks Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTime division multiple accessComputer scienceComputer networkQuality of serviceAlohaVariable bitrateNetwork packetThroughputReal-time computingChannel access methodJitterConstant bitrateWirelessTelecommunications

Abstract

fetched live from OpenAlex

This paper proposes data and voice scheduling algorithms for the dynamic reservation time division multiple access (DR-TDMA) MAC protocol for wireless ATM networks. Featuring a novel framed pseudo-Bayesian priority ALOHA algorithm that provides access priority to voice control packets, DR-TDMA improves the quality-of-service offered to voice connections and increases the maximum throughput for integrated voice and data traffic. The DR-TDMA protocol can also be extended to integrate constant bit rate (CBR) and variable bit rate (VBR) traffic in general. Simulation results show that the DR-TDMA protocol can achieve throughput in the range of 96% while maintaining reasonable quality of service for data traffic and a voice loss rate lower than 1%.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0020.001
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 head0.076
GPT teacher head0.341
Teacher spread0.265 · 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

Citations9
Published2003
Admission routes1
Has abstractyes

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