MétaCan
Menu
Back to cohort
Record W2116370098 · doi:10.1109/ccece.2006.277626

Distributed Dynamic Routing, Wavelength and Timeslot Assignment for Bandwidth on Demand in Agile All-Optical Networks

2006· article· en· W2116370098 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceComputer networkBandwidth (computing)Dynamic bandwidth allocationAgile software developmentMultiplexingWavelength-division multiplexingDistributed computingSurvivabilityChannel allocation schemesBlocking (statistics)Routing (electronic design automation)Network topologyBandwidth allocationRouting and wavelength assignmentWavelengthTelecommunicationsWireless

Abstract

fetched live from OpenAlex

In emerging agile all-optical networks, the next generation time division multiplexing technique in the optical domain is implemented on top of wavelength-division multiplexing to increase channel utilization and to support dynamic bandwidth demands. However, the corresponding dynamic routing, wavelength and timeslot assignment (DRWTA) problem has not yet been well addressed with respect to appropriately handling the bandwidth available. In this paper, we use dynamic programming and take the bottom-up approach to solve the DRWTA problem with the objective of minimizing blocking probability. We consider the ring topology and apply a distributed scheme to accommodate dynamic bandwidth requests in order to enhance network survivability and to decrease the degree of coordination among nodes. The proposed dynamic programming method decreases the runtime and improves time-related performance of the network

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score0.727

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 integrity0.0000.000
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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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

Quick stats

Citations6
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Optical Network TechnologiesFrench-language works237,207