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Record W2384099581

Transparent Transmission Technology and Applied Research of Ethernet

2009· article· en· W2384099581 on OpenAlexvenueno aff
Fujuan Li

Bibliographic record

VenueMicrocomputer applications · 2009
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsVirtual LANComputer scienceComputer networkEthernetCarrier EthernetTransmission (telecommunications)Metro EthernetQuality of serviceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This paper proposed the use of multiple-tag ways to achieve specific techniques and methods of Ethernet's transparent transmission,resolved the main limitation of Ethernet applications in the MAN and WAN.Through increased another layer of IEEE802.1Q VLAN tag out of the IEEE 802.1Q VLAN tag's outer layer,QinQ technology overcame the limitations of IEEE 802.1Q VLAN quantity space was too small,unable to provide the priority service,unable to realize user data transparent transmission and so on,promoted the application of the Metro Ethernet.In carrier network,QinQ technology's limitations were that operator's PE need to maintain the huge MAC address,to be unable to differentiate user BPDU and operator's BPDU,had only provided a very limited function of QoS and so on.Through the hierarchical address space,MAC in MAC technology had solved the QinQ's shortcomings,extended the network functionality and manageability,provided services for the operator's precision operation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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