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Record W2132727688 · doi:10.1109/hpsr.2001.923623

Routing in wavelength routed optical networks

2002· article· en· W2132727688 on OpenAlexaff
Y.P. Aneja

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLogical topologyComputer scienceTopology (electrical circuits)Network topologyStatic routingComputer networkRouting (electronic design automation)Hierarchical routingRouting tableDistributed computingRouting protocolMathematics

Abstract

fetched live from OpenAlex

We consider the routing problem that arises in the design of a virtual logical topology over a wavelength division multiplexed all optical network (AON). The logical topology is created by setting up lightpaths-end-to-end optical channels-created over the AON by suitable optical switching and routing. These lightpaths form the directed arcs of the logical topology. The combined problem of setting up lightpaths and routing of traffic over these lightpaths, in an optimal manner, is called the virtual topology design problem. The problem of designing such a topology and routing traffic over this topology with the objective of minimizing the network congestion while restricting the average propagation delay between source-destination pairs, and the degree of the logical topology, has been considered by Ramaswamy and Sivarajan (1996), and formulated as a large mixed linear integer program (MILP). For a given logical topology, the problem of optimal routing of traffic becomes a large linear program. We show that, by exploiting the special structure of this linear program, the routing problem can be managed and solved much more efficiently.

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 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 score0.781
Threshold uncertainty score0.506

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 head0.012
GPT teacher head0.202
Teacher spread0.189 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2002
Admission routes1
Has abstractyes

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