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Record W2110919149 · doi:10.1109/glocom.2006.365

OPN02-2: Inter-Group Shared Protection (I-GSP): A Scalable Solution for Survivable WDM Networks

2006· article· en· W2110919149 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

VenueGlobecom · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScalabilityComputer scienceInteger programmingLinear programmingRouting (electronic design automation)Distributed computingComputer networkUpper and lower boundsScheme (mathematics)Integer (computer science)Wavelength-division multiplexingPath (computing)Mathematical optimizationMathematicsAlgorithm

Abstract

fetched live from OpenAlex

The past studies for survivable routing suffers from the scalability problem when the number of nodes or connection requests grows in the network. In this proposal, a novel path based shared protection framework namely Inter-Group Shared protection (I-GSP) is developed such that the traffic matrix can be divided into multiple protection groups (PGs) based on specific grouping policy. This novel scheme not only overcomes the scalability problem but also provides an upper bound on the affected working paths in case of link failure in the network. Experiment results show that I-GSP based integer linear programming model solves the networks in a reasonable amount of time for which a regular integer linear programming formulation becomes computationally intractable. For most of the cases the performance gap between the optimal solution and the proposed I-GSP ranges between (2-16)%. The proposed optimization model yields a scalable and near-optimal solution for the capacity planning in the survivable optical networks.

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 score0.888
Threshold uncertainty score0.898

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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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