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Record W2043363978 · doi:10.1109/ccece.2008.4564601

A reliable routing protocol for agile All-Photonic Network

2008· article· en· W2043363978 on OpenAlexafffundvenue
Imad Khazali, Richard Vickers

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnhanced Interior Gateway Routing ProtocolComputer networkComputer scienceRouting tableDistributed computingRouting protocolZone Routing ProtocolDynamic Source RoutingPath vector protocolStatic routingLink-state routing protocolWireless Routing ProtocolHierarchical routingRouting (electronic design automation)

Abstract

fetched live from OpenAlex

This paper describes a routing protocol for the agile all-photonic network (AAPN). The protocol disseminates topology, reachability, and link state information to the edges of the network. The protocol facilitates building nodal routing tables at the edge nodes. A nodal routing table consists of two tables. Table one contains reachability information that allows an edge node to look up all the edge nodes to which a legacy node is connected. Table two contains a route set to every other edge node in the network ranked based on a cost criteria. The protocol supports the deployment of an overlay interconnection model with legacy networks where routing in the AAPN network is independent from routing in the client network. The protocol relies on the ASRSP signalling protocol control messages for fault detection that facilitates fast routing table update in case of failures in the network.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.024
GPT teacher head0.223
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2008
Admission routes3
Has abstractyes

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