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Record W2138039764 · doi:10.1109/mnet.2008.4694173

Trends in Optical Switching Techniques: A Short Survey

2008· article· en· W2138039764 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

VenueIEEE Network · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBottleneckComputer science10G-PONOptical burst switchingTelecommunicationsOptical switchMultiwavelength optical networkingBandwidth (computing)Optical performance monitoringPower consumptionPassive optical networkOptical cross-connectComputer networkOptical fiberElectronic engineeringWavelength-division multiplexingPower (physics)Fiber optic splitterEngineeringEmbedded systemMaterials science

Abstract

fetched live from OpenAlex

We are currently witnessing a strong worldwide push toward bringing fiber closer to individual homes and businesses. The emerging FTTX access networks will move the bandwidth bottleneck from the first/last mile toward metropolitan and wide area networks, creating a need for efficient optical-switching mechanisms. In this article, we review the current trends in optical switching that help to improve the bandwidth efficiency, as well as to decrease the cost and power consumption of next-generation optical networks. Our review provides an overview of the optical switching domain and facilitates the understanding of newly emerging switching techniques and their interpretation as derivatives of the presented main optical switching trends.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.260
Teacher spread0.233 · 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