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Record W2058226996 · doi:10.1109/mcom.2014.6852092

Design considerations for managing wide area software defined networks

2014· article· en· W2058226996 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

VenueIEEE Communications Magazine · 2014
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkRouterSoftware-defined networkingBottleneckNetwork packetNetwork architectureNetwork managementDistributed computingController (irrigation)Networking hardwareEmbedded system

Abstract

fetched live from OpenAlex

SDN has the potential to simplify network configuration and reduce management complexity. In today¿s networks control and forwarding functions are tightly coupled and embedded within each switch/router. SDN, in contrast, accumulates the control functionality in one or more dedicated network entities called controllers, which provide a unified interface to configure and control the network. Packet forwarding, on the other hand, remains the responsibility of the switches/routers. Many datacenter networks have benefited from the abstraction provided by SDN. However, in a Wide Area Network (WAN) a single controller becomes a performance bottleneck. Multiple controller solutions are proposed as a natural consequence. In this article we present the requirements, design alternatives, and a possible management architecture for a single administrative domain WA-SDN. We also discuss the functional components that should be present in a multi-controller architecture for managing WA-SDN deployments.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.562
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.061
GPT teacher head0.268
Teacher spread0.207 · 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