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Record W2079279729 · doi:10.1109/ccnc.2012.6180997

Open virtual playground: Initial architecture and results

2012· article· en· W2079279729 on OpenAlexaff
May El Barachi, Nadjia Kara, Rachida Dssouli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsConcordia UniversityÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceVirtualizationVirtual networkQuality of serviceArchitectureService (business)Network virtualizationComputer networkNetwork architectureVoice over IPNetwork serviceDistributed computingWorld Wide WebCloud computingThe InternetOperating system

Abstract

fetched live from OpenAlex

Network virtualization is a promising and technically challenging concept, which enables the dynamic creation of several co-existing logical network instances (or virtual networks) over a shared physical network infrastructure. There are several motivations behind this concept, including: cost-effective sharing of resources; customizable networking solutions; and the convergence of existing network infrastructures. We have previously proposed a new business model for virtual networking environments. In this paper, we use this model as well as concrete use cases as basis for the definition of the Open Virtual Playground - an open virtual multi-services networking architecture in which different levels of services (i.e. essential services, service enablers, service building blocks, and end-user services) offered by various players, can be dynamically discovered, used, and composed. Furthermore, a QoS-enabled VoIP service scenario is used to demonstrate the system operation and preliminary performance measurements are collected.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.348

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 communication0.0000.001
Open science0.0010.001
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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2012
Admission routes1
Has abstractyes

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