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Record W2114540026 · doi:10.1109/icc.2002.997355

An analytical model for predicting the locations and frequencies of 3R regenerations in all-optical wavelength-routed WDM networks

2003· article· en· W2114540026 on OpenAlex
N. Barakat, Alberto Leon‐Garcia

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
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProvisioningWavelength-division multiplexingComputer scienceNode (physics)Network topologyComputer networkPath (computing)Routing protocolRouting (electronic design automation)Routing and wavelength assignmentTopology (electrical circuits)WavelengthDistributed computingElectronic engineeringEngineeringOpticsPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In all-optical wavelength-switched WDM networks, 3R regeneration does not need to be performed at every node in a path. Thus, a significant cost savings can be realized by efficiently provisioning a limited amount of 3R regeneration resources in each node in the network and utilizing these resources efficiently. In order to aid in these two tasks, we present an analytical model to predict the location and relative frequency of 3R regeneration requests in the network. Because the model is based solely on the topological information of the network, the predictions provided are very general and are independent of specific network operating parameters, such as the routing protocol employed. Simulation results are also presented to verify the accuracy of the model.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.688
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.033
GPT teacher head0.269
Teacher spread0.236 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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