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Record W1810000146 · doi:10.3233/hsn-2002-216

A scalable logical topology for optical networks

2002· article· en· W1810000146 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

VenueJournal of High Speed Networks · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceScalabilityTopology (electrical circuits)Computer networkLogical topologyNetwork topologyDistributed computingTheoretical computer scienceOperating systemElectrical engineering

Abstract

fetched live from OpenAlex

One of the approaches investigated for multihop lightwave networks is to consider regular graphs as the logical topology for a multihop network. Standard regular topologies are defined only for networks with the number of nodes satisfying some rigid criteria and are not directly usable for multihop networks. Only a few recent proposals (e.g., GEMNET) are regular and yet allow the number of nodes to have any arbitrary value. These networks have one major problem – node addition requires a major redefinition of the network. For example, in a multistar implementation, a large number of retuning of transmitters and receivers and/or renumbering nodes are needed for GEMNET. In this paper we present a new logical topology which has a low diameter but is not strictly regular. The interesting aspect of this topology is that it allows the network to be expanded incrementally involving a relatively small number of edge definitions/redefinitions. In this paper we have described our new topology and its properties. We have also implemented a routing scheme that ensures a low diameter and an algorithm for adding nodes to 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.

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 score0.854
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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