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Record W2165651458 · doi:10.1109/jsac.2004.830465

A Multilayer Differentiated Protection Services Architecture

2004· article· en· W2165651458 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

VenueIEEE Journal on Selected Areas in Communications · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsLakehead UniversityUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceComputer networkDistributed computingScalabilityProtocol stackNetwork architectureDifferentiated servicesBandwidth (computing)ArchitectureWireless sensor networkQuality of serviceDatabase

Abstract

fetched live from OpenAlex

Metropolitan area and long-haul networks are migrating toward the deployment of optical mesh technologies. This requires, among other things, a new generation of highly intelligent protection and restoration mechanisms to perform functions of protection and bandwidth management. We introduce an architecture that provides differentiated protection services across multiple layers of network hierarchy. A connection at any client layer can request a protection against resource failures at any lower layer. A key aspect of the architecture is the hierarchical tree organization of shared risk link group (SRLG) resources. They represent routing-related failures across all layers of protocol stack. The architecture is very scalable in terms of communicating link-state and bandwidth information between adjacent layers. SRLG trees are used to aggregate this information and provide a summary to the client layer. We discuss the requirements and challenges for routing and signaling mechanisms in order to support the proposed architecture. The complexity of this architecture is evaluated and compared with the complexity of a nonhierarchical alternative.

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 score0.369
Threshold uncertainty score0.739

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 science0.0010.000
Research integrity0.0000.002
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 head0.019
GPT teacher head0.253
Teacher spread0.235 · 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