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Record W2103738403 · doi:10.1109/glocom.2004.1378041

Dynamic threshold-based call admission framework for prioritized multimedia traffic in wireless cellular networks

2005· article· en· W2103738403 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 institutionsQueen's University
Fundersnot available
KeywordsComputer scienceComputer networkHandoverQuality of serviceCall Admission ControlBase stationWireless networkBandwidth (computing)Cellular networkOverhead (engineering)WirelessMulti-frequency networkCellular trafficScalabilityAdmission controlCall blockingDistributed computingHeterogeneous networkTelecommunications

Abstract

fetched live from OpenAlex

Next generation wireless cellular networks aim at supporting wireless multimedia services with different classes of traffic that are characterized by diverse quality of service (QoS) and bandwidth requirements. They will use micro/picocellular architectures in order to provide higher capacity. However, small-size cells increase the handoff rate drastically. As a result, it is a challenge to provide stable QoS in these networks. In this paper, we present a novel dynamic call admission control (DyCAC) framework for next generation wireless cellular networks. The framework consists of the following components: (i) a threshold-based bandwidth reservation policy; (ii) a threshold update processing module; and (iii) an admission controller module. In this work, each base station locally, independently of other base stations in the network, differentiates between new and handoff calls for each class of traffic by assigning a threshold to each class according to its QoS requirements. The threshold values change dynamically and periodically in order to respond to the varying traffic conditions. The main feature of the proposed framework is its ability to simultaneously achieve several design goals. Numerical results show that our proposed DyCAC framework can guarantee the connection-level quality of service of individual traffic classes while maximizing resource utilization. As well, DyCAC requires low communication overhead, and is highly scalable.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0030.000
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 head0.304
Teacher spread0.284 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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