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Record W2156176312 · doi:10.1109/cnsr.2006.19

Bandwidth Provisioning and Capacity Planning Tools

2006· article· en· W2156176312 on OpenAlexafffund
J. Almhanaa, Zhen Liua, R. McGormanb, B. Lanteignea

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of CanadaAtlantic Canada Opportunities Agency
KeywordsProvisioningBandwidth (computing)Computer scienceQuality of serviceComputer networkThe InternetBandwidth allocationVoice over IPTelecommunicationsWorld Wide Web

Abstract

fetched live from OpenAlex

Bandwidth provisioning is an important issue for Internet service providers (ISPs) and ensuring quality of service (QoS) is a major concern. QoS is closely related to the available bandwidth which itself is subject to financial constraints. Unfortunately, up to now there have been no adequate tools available in the market so that ISPs can do accurate bandwidth provisioning. In this paper, we describe the software tools developed by GRETI for that purpose. These tools provide several calculators for voice over IP and data traffic

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.014

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 head0.207
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2006
Admission routes2
Has abstractyes

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