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Record W2109348731 · doi:10.1002/dac.801

VoIP over WLAN: voice capacity, admission control, QoS, and MAC

2006· article· en· W2109348731 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

VenueInternational Journal of Communication Systems · 2006
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of VictoriaUniversity of Waterloo
Fundersnot available
KeywordsVoice over IPComputer scienceComputer networkQuality of serviceTelecommunicationsWireless Multimedia ExtensionsThe InternetWirelessTelephonyCall Admission ControlWi-FiWireless networkWi-Fi arrayWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Voice over Internet Protocol (VoIP) is one of the fastest growing Internet applications. It is a viable alternative to the traditional telephony systems due to its high resource utilization and cost efficiency. Meanwhile, Wireless Local Area Networks (WLANs) have become a ubiquitous networking technology that has been deployed around the world. Driven by these two popular technologies, Voice over WLAN (VoWLAN) has been emerging as an infrastructure to provide low‐cost wireless voice services. However, VoWLAN poses significant challenges since the performance characteristics of wireless networks are much worse than that of their wireline counterparts, and the IEEE 802.11‐based WLAN was not originally designed to support delay‐sensitive voice traffic. In this paper, we provide a survey of recent advances in VoWLAN voice capacity analysis, call admission schemes, and medium access control (MAC) layer quality of service (QoS) enhancement mechanisms. Some open research issues are presented for further investigation. Copyright © 2006 John Wiley & Sons, Ltd.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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