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Record W2153122394 · doi:10.1109/iscc.2005.72

Flexible Bandwidth Provision in a Sectored Packet Switch with an Optical Core

2005· article· en· W2153122394 on OpenAlexafffund
Sofia A. Paredes, Trevor J. Hall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Ottawa
FundersConsejo Nacional de Ciencia y TecnologíaCanada Research ChairsUniversity of Cambridge
KeywordsPhotonicsBottleneckComputer scienceControl reconfigurationNetwork packetOptical switchBandwidth (computing)Packet switchingArchitectureElectronic engineeringComputer networkEngineeringEmbedded systemOpticsPhysics

Abstract

fetched live from OpenAlex

An opto-electronic three-stage packet switch architecture is described that plays to the strengths of electronics as a memory technology and to photonics as a communications technology whilst accommodating the relatively slow reconfiguration of current transparent photonic switch technology. The configuration of the photonic centre stage is found by solving an edge-colouring problem on a bipartite graph defined by the traffic. This is simple to implement and the calculation need be repeated only if there are persistent variations in the statistical pattern of the arriving traffic. A major bottleneck is removed by dispensing with a per-time slot scheduler; at the price of only a modest spatial speed-up, which is easy to provide with photonic technology. The architecture and method have been verified by simulation using simple traffic models that capture the non-stationary and bursty nature of real 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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.241
Teacher spread0.227 · 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
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

Citations1
Published2005
Admission routes2
Has abstractyes

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