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Record W2001025765 · doi:10.1109/bsc.2008.4563212

Service reliability with enhanced failure recovery rate for multiple failures in survivable optical networks

2008· article· en· W2001025765 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
KeywordsFailure rateBackupService recoveryService (business)Reliability engineeringComputer scienceReliability (semiconductor)Computer networkRecovery rateSurvivabilityEngineeringService qualityBusinessOperating system

Abstract

fetched live from OpenAlex

In this paper, two basic parameters of service reliability, called service availability and service disruption rate against disjoint primary and backup paths failure in survivable optical networks are studied. The service availability and service disruption rate affected by dasiaenhanced failure recovery rate for multiple failurespsila is considered here. We consider enhanced failure recovery rate for multiple failures where a higher failure recovery rate is applied, if more than one path fail. Results of this paper can be divided into two parts. First, higher service availability can be achieved by dasiaenhanced failure recovery rate for multiple failurespsila. Secondly, reduction of the service disruption rate by increasing the dasiaenhanced failure recovery rate for multiple failurespsila is negligible. Therefore, this method is more applicable where connection availability is more important than that of the service disruption rate.

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 score0.329
Threshold uncertainty score0.901

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 integrity0.0000.000
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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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
Published2008
Admission routes1
Has abstractyes

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