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Record W2040100434 · doi:10.1117/12.778931

The impact of stale information on the blocking performance of dynamic routing, wavelength and timeslot assignment schemes for bandwidth on demand in metro agile all-optical ring networks

2007· article· en· W2040100434 on OpenAlexaff
Wei Yang, Sofia A. Paredes, Trevor J. Hall

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceComputer networkDynamic bandwidth allocationBandwidth allocationWavelength-division multiplexingBlocking (statistics)Bandwidth (computing)MultiplexingOptical networkingOverhead (engineering)Distributed computingTelecommunicationsWavelength

Abstract

fetched live from OpenAlex

In emerging agile all-optical networks, where time division multiplexing (TDM) in the optical domain is implemented on top of wavelength-division multiplexing (WDM) to improve the network utilization and to support dynamic bandwidth demands, a control mechanism is required to handle the setup and tear down of fast flexible all-optical connections. In this paper, we propose two control protocols for WDM-TDM all-optical ring networks based on whether or not global network information is available. For the global information based protocol, we choose a periodic state-updating mechanism to confine the control message overhead within a reasonable range. For the local information based protocol, we select a backward reservation scheme for dynamic routing, wavelength and timeslot assignment (DRWTA) algorithms to prevent bandwidth overbooking. By conducting extensive numerical simulations, we investigate the impact of imprecise information on the blocking probability of the DRWTA algorithms for the two protocols. Our simulation results show that the local information based protocol outperforms the global information based protocol for metro all-optical networks where propagation delay is small compared to the service time of requests.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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.

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
Published2007
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