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Record W2164922601 · doi:10.1109/icumt.2009.5345601

Demand-wise shared protection network design with dual-failure restorability

2009· article· en· W2164922601 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 Alberta
Fundersnot available
KeywordsSurvivabilityComputer scienceDual (grammatical number)Core (optical fiber)Digital signal processingRouting (electronic design automation)Computer networkReliability engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

The availability requirements placed on core communication networks have been rapidly increasing. As the value of the traffic served by these core networks has increased so has the impact of failure. Demand-wise shared protection (DSP) was developed to provide failure survivability in the network that was more efficient than concurrently routing two paths of traffic (1+1 APS), yet was more straightforward to manage than more complex schemes. The DSP model was adapted to ensure, in addition to 100% single failure survivability, a specified minimum level of dual-failure restorability. The effect of enforcing dual-failure restorability in DSP networks was evaluated in terms of cost and overall increases in availability. Counter-intuitively, it was found that in some cases, requiring some specified dual-failure restorability levels can result in decreased availability. DSP was effectively adapted to ensure dual-failure restorability, however, in order to capitalize on the capacity sharing aspects of the model, networks must be sufficiently well connected.

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: Methods · Consensus signal: none
Teacher disagreement score0.542
Threshold uncertainty score0.578

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 head0.016
GPT teacher head0.207
Teacher spread0.191 · 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
Published2009
Admission routes1
Has abstractyes

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