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Record W1972849324 · doi:10.1109/ewsdn.2012.17

Software-Defined Networking: Experimenting with the Control to Forwarding Plane Interface

2012· article· en· W1972849324 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsSolana Networks (Canada)
Fundersnot available
KeywordsOpenFlowForwarding planeRouting control planeComputer scienceSoftware-defined networkingInterface (matter)Computer networkDistributed computingProtocol (science)SoftwareConvergence (economics)Operating system

Abstract

fetched live from OpenAlex

Software-Defined Networking (SDN) is an emerging network architecture where the network control plane is decoupled from the forwarding plane and is programmable via an open protocol. Forwarding and Control Element Separation (Forces) first and OpenFlow later are the prevailing protocols that enable this separation. The differences between the two stem from the underlying models they are defined upon. While OpenFlow is widely used, its capability for adding new functionality of the Forwarding plane is questionable, a fact that is attributed to a restricted model. In contrast, Forces has a very dynamic model that makes its protocol quite powerful but has known little spread due to lack of industry adoption and in the academic world due to lack of open source availability for experimentation. In this paper we first investigate ways of possible confluence or convergence of Forces and OpenFlow and later we explore a real-life service use case for applying a Enabled-enabled OpenFlow switch.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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

Quick stats

Citations20
Published2012
Admission routes1
Has abstractyes

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