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Record W2159149320 · doi:10.1109/glocom.2007.956

On Optimal Admission Control for Multi-Service Cellular/WLAN Interworking

2007· article· en· W2159149320 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 scienceQuality of serviceComputer networkAdmission controlCall Admission ControlCellular networkChannel (broadcasting)Service (business)Wireless networkWirelessTelecommunications

Abstract

fetched live from OpenAlex

The complementary characteristics of cellular systems and wireless local area networks (WLANs) make them attractive candidates to jointly offer a seamless wireless solution. In an integrated cellular/WLAN system, the quality of service (QoS) requirements for different services (e.g., voice and real-time video) require adequate admission control policies to limit the number of connections in each network. In this paper, we analytically develop a comprehensive model to facilitate the optimal evaluation of different admission control policies in a multi-service integrated cellular/WLAN system. Given the model, we formulate two optimization problems to adjust admission control parameters. The first problem is to maximize the network revenue while the second problem is to minimize the required network resources subject to QoS constraints. We evaluate each problem when different combinations of cutoff priority and fractional guard channel admission control policies are being used. We show that a combination of two cutoff priority policies achieves the best solution for both problems.

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 score0.963
Threshold uncertainty score0.438

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 communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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