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Record W2101467233 · doi:10.1109/vetecf.2003.1285308

Adaptive resource management for multimedia wireless networks

2003· article· en· W2101467233 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBandwidth (computing)Computer networkDynamic bandwidth allocationCall blockingBandwidth allocationWirelessBlocking (statistics)Scheme (mathematics)Bandwidth managementWireless networkAdaptation (eye)Call Admission ControlQuality of serviceDistributed computingMultimediaTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

This paper proposes an adaptive resource management scheme for multimedia services in a wireless network environment. The proposed scheme attempts to allocate the desired bandwidth to every multimedia connection originating in a cell or being handed off to the cell. In case of insufficient bandwidth and in order not to deny service to requesting connections, bandwidth adaptation is done. However, to improve upon the hand-off dropping probability, the proposed bandwidth adaptation algorithm has a provision for giving preference to hand-off calls over new calls. The scheme also ensures that the borrowed bandwidth is promptly returned to the degraded connections. Simulation results show that the proposed scheme outperforms the previous known schemes in terms of call dropping probability, call blocking probability and bandwidth utilization.

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 score0.899
Threshold uncertainty score0.503

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 science0.0020.000
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 head0.032
GPT teacher head0.279
Teacher spread0.247 · 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

Citations16
Published2003
Admission routes2
Has abstractyes

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