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Record W1504553246

Reliable fiber-wireless access networks: Less an end than a means to an end

2013· article· en· W1504553246 on OpenAlexaff
Martin Maier

Bibliographic record

VenueDesign of Reliable Communication Networks · 2013
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsSmart gridDependabilityTelecommunicationsAccess networkWirelessComputer scienceWireless networkComputer networkBroadbandEnd userWireless broadbandEngineeringElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

In coming years, broadband access networks are expected to undergo a couple of paradigm shifts. First, copper will play a less important role and eventually give way to bimodal fiber-wireless (FiWi) access networks. Second, broadband access networks will become less an end in itself than a means to an end by exploiting them not only for telecommunications per se but also other relevant economic sectors of the future low carbon society. Despite recent research activities demonstrating that both fiber and wireless media might be also used to transfer small amounts of energy over limited distances, it is anticipated that fiber and wireless technologies represent the two remaining complementary building blocks of future converged communications networks, while copper remains the energy (but not necessarily data) transmission medium of choice in future smart power grids. In this paper, we explore ways of using dependent FiWi access networks to enable or enhance the dependability of other critical infrastructures of today's society, most notably the future smart power grid. After discussing the respective pros and cons of a variety of available access networking technologies, we elaborate on the rationale behind the design choices of our Uber-FiWi network and showcase its suitability as a holistic end-to-end smart grid communications infrastructure for next-generation power distribution networks via illustrative experimental and co-simulation studies on emulated power blackouts during a security breach and coordinated plug-in electric vehicle (PEV) charging without a deviated voltage profile and deteriorated power quality.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0040.001
Research integrity0.0000.001
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 head0.036
GPT teacher head0.265
Teacher spread0.228 · 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.

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

Citations9
Published2013
Admission routes1
Has abstractyes

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