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Record W3132297685 · doi:10.1017/cbo9780511619731

Optical Switching Networks

2008· book· en· W3132297685 on OpenAlexaff
Martin Maier

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer networkOptical burst switching10G-PONComputer scienceMultiprotocol Label SwitchingOptical cross-connectOptical Transport NetworkOptical networkingOptical performance monitoringEthernetOptical switchPassive optical networkMultiwavelength optical networkingLabel switchingTelecommunicationsElectronic engineeringWavelength-division multiplexingEngineeringOptical fiberFiber optic splitterPhysicsOptoelectronicsQuality of service

Abstract

fetched live from OpenAlex

Optical Switching Networks describes all the major switching paradigms developed for modern optical networks, discussing their operation, advantages, disadvantages and implementation. Following a review of the evolution of optical WDM networks, an overview of the future trends out. The latest developments in optical access, local, metropolitan, and wide area networks are covered, including detailed technical descriptions of generalized multiprotocol label switching, waveband switching, photonic slot routing, optical flow, burst and packet switching. The convergence of optical and wireless access networks is also discussed, as are the IEEE 802.17 Resilient Packet Ring and IEEE 802.3ah Ethernet passive optical network standards and their WDM upgraded derivatives. The feasibility, challenges and potential of next-generation optical networks are described in a survey of state-of-the-art optical networking testbeds. Animations showing how the key optical switching techniques work are available via the web, as are lecture slides (www.cambridge.org/9780521868006).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.078
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0780.058

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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations70
Published2008
Admission routes1
Has abstractyes

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