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Record W641618483 · doi:10.1016/j.procs.2015.05.027

Analysis on the Effect of Adopting Green SLA on Optical WDM Networks

2015· article· en· W641618483 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

VenueProcedia Computer Science · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceWavelength-division multiplexingTelecommunicationsComputer networkOptoelectronicsWavelength

Abstract

fetched live from OpenAlex

This paper analyzes the effect of Green Service Level Agreement (GSLA) on resource efficiency and emission reduction of wavelength-division multiplex (WDM) optical networks governed by Generalized Multi-Protocol Label Switching (GMPLS). Green routing mechanisms may use more resources in serving equal number of connection requests in optical networks, which makes them less favorable for Internet and infrastructure providers. This work shows that the usage of green and hybrid routing mechanism is in fact more resource efficient than using traditional non-green routing methods by simply choosing the greenest route. The amount of greenness of routes in optical networks is requested through GSLA mandating service providers to provide routes for connection requests that are being powered ON by at least certain amount of green energy such as solar energy.

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)0.001
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 score0.603
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.227
Teacher spread0.215 · 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