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Record W2140437454 · doi:10.1186/s13677-015-0029-5

A service oriented broker-based approach for dynamic resource discovery in virtual networks

2015· article· en· W2140437454 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

VenueJournal of Cloud Computing Advances Systems and Applications · 2015
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsConcordia UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceNetwork virtualizationVirtualizationCloud computingProof of conceptVirtual networkDistributed computingThe InternetService (business)Resource (disambiguation)Network architectureVirtual machineWorld Wide WebComputer networkOperating system

Abstract

fetched live from OpenAlex

Abstract In the past few years, the concept of network virtualization has received significant attention from industry and research fora. This concept applies virtualization to networking infrastructures by enabling the dynamic creation of several co-existing logical network instances (or virtual networks) over a shared physical network infrastructure (or substrate network). Due to the potential it offers in terms of diversifying existing networks and ensuring the co-existence of heterogeneous network architectures on top of shared substrates, network virtualization is often considered as an enabler of a polymorphic Internet and a cornerstone of the future Internet architecture. One of the challenges associated with the network virtualization concept is the description, publication, and discovery of virtual resources that can be composed to form virtual networks. To achieve those tasks, there is a need for an expressive information model facilitating information representation and sharing, as well as an efficient resource publication and discovery framework. In this paper, we propose a service oriented, broker-based framework for virtual resource description, publication, and discovery. This framework relies on a novel service-oriented hierarchical business model and an expressive information model for resources/services description. The detailed framework’s architecture is presented, and its operation is illustrated using a REST-based content distribution scenario. Furthermore, a proof-of-concept prototype implementation realized using various technologies/tools (e.g. Jersey, JAXB, PostgreSQL, and Xen cloud platform) is presented along with a detailed performance analysis of the system. When compared to existing virtual resource discovery frameworks, our broker-based virtual resource discovery framework offers signification performance improvements of the virtual resources’ discovery operation, in terms of response time (92.8% improvement) and incurred network load (77.3% improvement), when dealing with multiple resource providers. Furthermore, relying on a broker as intermediary role simplifies the resources’ discovery and selection operations, and improves the overall efficiency of the virtual network embedding process.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.260
Teacher spread0.245 · 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