MétaCan
Menu
Back to cohort
Record W2041154714 · doi:10.1117/12.630014

An integrated architecture enabling different resource sharing schemes for AAPN networks

2005· article· en· W2041154714 on OpenAlexaff
M. Jin, Ou Yang

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceStar networkNode (physics)Network topologyComputer networkTime-division multiplexingOptical switchOptical burst switchingPassive optical networkMultiplexingOptical performance monitoringScheduling (production processes)Wavelength-division multiplexingElectronic engineeringEngineeringRing networkTelecommunicationsWavelength

Abstract

fetched live from OpenAlex

The single-hop star-based network is proposed as a feasible topology to fit the rapidly-increasing bandwidth requirement in the AAPN research project. This paper investigates the node architecture to implement all-optical operations in such a network using available technologies. Based on the node placement in the network, two architectures are designed, one is placed in the edge and another one is used in the core. The edge node is a multi-stage electronic/optic switch, which aggregates legacy traffics and transmits them to the core node, or accepts optical messages from the core node and sends them to legacy networks. Each stage uses either electronic or optical components to implement signal storage, conversion or transmission. The core node is an all-optical switch which switches optical signals in different wavelength planes, while the controlling part works in electronic domain. A separate control plane is designed to manipulate the operation of different component devices. This system provides a common platform for the overlaid-star network. By introducing synchronization or not, we can employ reservation-based optical time-division-multiplexing (OTDM) or contention-based optical burst switching (OBS) in the designed architecture. No wavelength conversion or optical buffering is necessary by agilely scheduling the messages in both mechanisms. Our research is an efficient and feasible solution which satisfies the transmission requirement by taking into account of technological availability. Our design is supported by the performance evaluation of OTDM and OBS methods, and their comparisons under different scenarios.

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 score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Optical Network TechnologiesFrench-language works237,207