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Record W2126940261

Virtual topology design for flexible periodic traffic demands

2011· article· en· W2126940261 on OpenAlexaff
Ying Chen, Michael H. Hall, Arunita Jaekel

Bibliographic record

VenueEuropean Conference on Networks and Optical Communications · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsNetwork topologyComputer scienceTopology (electrical circuits)Scheduling (production processes)Logical topologySet (abstract data type)Integer programmingTopology optimizationDistributed computingMathematical optimizationComputer networkEngineeringMathematicsAlgorithm
DOInot available

Abstract

fetched live from OpenAlex

In recent years, two possible approaches have been investigated for solving the virtual topology design problem for periodic (multi-hour) traffic demands. The first approach attempts to design a static topology that can accommodate all the traffic variations over time. The second option is to determine an appropriate series of virtual topologies to accommodate the different traffic loads at different times. This can lead to some cost savings in terms of the number of transceivers needed, but it requires the use of costly reconfigurable switching equipment. In this paper we present an integer linear program (ILP) formulation for designing an optimal, stable virtual topology for time-varying demands. Unlike previous work in the area, we consider the case where the exact start and end times of the demands are not known beforehand, but can slide within a larger time window. Our novel design approach integrates the topology design problem with proper scheduling of the demands in time, to create an optimal static topology capable of handling the set of periodic traffic demands.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.717

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.092
GPT teacher head0.269
Teacher spread0.177 · 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
GenreMethods

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

Citations2
Published2011
Admission routes1
Has abstractyes

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