Provendo uma Infraestrutura de Software Fatiada, Isolada e Segura de Funções Virtuais através da Tecnologia de Corrente de Blocos
Bibliographic record
Abstract
As tecnologias de fatiamento da rede (Network Slicing), virtualização de funções de rede (Network Function Virtualization - NFV) e redes definidas por software (Software-Defined Networking - SDN) proveem serviços fim-a-fim ágeis e sob demanda. A identificação de uma função virtual defeituosa torna-se obrigatória, pois serviços alocam recursos em um ambiente distribuído e sem confiança entre os pares composto por múltiplos inquilinos e provedores de serviço concorrentes. Este artigo propõe e desenvolve uma arquitetura baseada em correntes de blocos para prover auditabilidade às operações de orquestração de fatias de rede. Um protótipo de um caso de uso foi desenvolvido e implementado utilizando a plataforma Hyperledger Fabric na qual cada fatia de rede opera sobre um canal isolado. Os resultados mostram que é possível prover segurança à criação de fatias de rede, mas que a obtenção de consenso e o número de transações requeridas pelas fatias de rede são um grande desafio.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".