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Record W4251965956 · doi:10.1002/9781119183587.ch17

NG MVPN

2015· other· en· W4251965956 on OpenAlexaff
Glenn Warnock B.Sc., Mira Ghafary B.Sc., Ghassan Shaheen M.Sc.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMulticastComputer networkIdentifierRouterComputer science

Abstract

fetched live from OpenAlex

This chapter describes the Next Generation MVPN (NG MVPN) approach to multicast VPN in SR OS (Alcatel-Lucent Service Router Operating System). NG MVPN is a standardized and more generalized approach to MVPN that effectively supersedes Draft Rosen. NG MVPN uses BGP Auto-Discovery (A-D) to discover MVPN members, and either PIM/GRE or MPLS point-to-multipoint (P2MP) LSPs to transport multicast data. The tunnel identifier field varies depending on the tunnel type. The tunnel identifier field is described in more detail later. Although PIM is still an option for building the I-PMSI and S-PMSI MDTs in an NG MVPN, MP-BGP is the primary protocol used for signaling. NG MVPN uses MP-BGP to discover the member PEs. Until now, the tree used to transport customer data across the core has been a PIM MDT. With the use of BGP for handling customer PIM signaling, PIM is not required in the service provider core.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.227
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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