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Record W4235181959 · doi:10.1002/dac.1124

Performance analysis of a cell‐based call admission control scheme for QoS support in multimedia wireless networks

2010· article· en· W4235181959 on OpenAlexaff
Nidal Nasser, Sghaier Guizani

Bibliographic record

VenueInternational Journal of Communication Systems · 2010
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceComputer networkCall Admission ControlHandoverQuality of serviceBandwidth (computing)Queueing theoryAdmission controlBandwidth allocationWirelessCall blockingProvisioningWireless networkBlocking (statistics)Telecommunications

Abstract

fetched live from OpenAlex

Abstract Next generation wireless communication systems, including 3G and 4G technologies, are envisaged to support more mobile users and a variety of high‐bandwidth multimedia services. Different multimedia services have diverse bandwidth and quality of service (QoS) requirements from their users that need to be guaranteed by wireless cellular systems. Furthermore, these systems will use micro/pico cellular architecture to provide a higher capacity. As a result of the smaller coverage area of this architecture, handoff events will occur at a much higher rate compared with the present macrocellular systems. In this paper, a multiple‐threshold bandwidth reservation scheme combined with a call admission control algorithm is proposed and analyzed. The objective of our work is to achieve better QoS provisioning for mobile users while achieving efficient utilization of the available limited bandwidth. The proposed scheme is modeled as M/M/C/C queueing system and the performance measures, call blocking probability (CBP), and call dropping probability (CDP) are computed. The performance of our scheme is compared with the Complete Sharing (CS) policy. Simulation results show that our scheme surpasses the CS policy in terms of CBP, CDP, and bandwidth utilization. Copyright © 2010 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.

How this classification was reachedexpand

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)0.003
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 score0.687
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0050.000
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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2010
Admission routes1
Has abstractyes

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