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Record W2525816948 · doi:10.15598/aeee.v14i3.1781

On the Highly Stable Performance of Loss-Free Optical Burst Switching Networks

2016· article· en· W2525816948 on OpenAlex
Miloš Kozák, Brigitte Jaumard, Leoš Boháč

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvances in Electrical and Electronic Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia UniversityČeské Vysoké Učení Technické v Praze
KeywordsOptical burst switchingOptical switchBurst switchingComputer scienceMaterials scienceOptoelectronicsTelecommunicationsOptical performance monitoringWavelength-division multiplexingTransmission delay

Abstract

fetched live from OpenAlex

Increase of bandwidth demand in data networks, driven by the continuous growth of the Internet and the increase of bandwidth greedy applications, raise the issue of how to support all the bandwidth requirements in the near future. Three optical switching paradigms have been defined and are being investigated: Optical Circuit Switching (OCS); Optical Packet Switching (OPS); and Optical Burst Switching (OBS). Among these paradigms, OBS is seen as the most appropriate solution today. However, OBS suffers from high burst loss as a result of contention in the bufferless mode of operation. This issue was investigated by Coutelen et al., 2009 who proposed the loss-free CAROBS framework whereby signal convertors of the optical signal to the electrical domain ensure electrical buffering. Convertors increase the network price which must be minimized to reduce the installation and operating costs of the CAROBS framework. An analysis capturing convertor requirements, with respect to the number of merging flows and CAROBS node offered load, was carried out. We demonstrated the convertor location significance, which led to an additional investigation of the shared wavelength convertors scenario. Shared wavelength convertors significantly decrease the number of required convertors and show great promise for CAROBS. Based on this study we can design a CAROBS network to contain a combination of simple and complex nodes that include none or some convertors respectively, a vital feature of network throughput efficiency and cost.

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: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.002
GPT teacher head0.175
Teacher spread0.172 · 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