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Record W2148023445 · doi:10.1109/ccece.2008.4564777

On all-optical slot switching with partial alignment

2008· article· en· W2148023445 on OpenAlexvenueno aff
Soung‐Yue Liew

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsOptical switchComputer scienceNetwork packetCoupling (piping)Optical burst switchingOptical performance monitoringTopology (electrical circuits)Electronic engineeringOpticsPhysicsMaterials scienceComputer networkWavelength-division multiplexingEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Most all-optical cell (or, fixed-length) switching schemes require incoming cells to be exactly aligned to slot boundaries through the use of optical aligners. However, such form of exact alignment is impractical in an all-optical environment as the optical aligners may require an infinite number of aligning stages to perfectly align the uncoordinated arriving cells. We show that partial alignment is a more practical solution. In partial alignment, a limited number of aligning stages is employed in each optical partial aligner. Coupling with the reduced cell size (which is smaller than the slot size), we are able to achieve performance close to that of perfectly aligned packet switch. We then demonstrate its performance through simulation.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.981
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.014
GPT teacher head0.177
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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2008
Admission routes1
Has abstractyes

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