Repositorio Universidad del Cauca

Autonomic classification of IP traffic in an NFV-based network

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dc.contributor.author Martínez Ordóñez, María Camila es
dc.contributor.author Vergara Reyes, Juliana Alejandra es
dc.date.accessioned 2019-11-19T15:56:31Z
dc.date.available 2019-11-19T15:56:31Z
dc.date.issued 2017
dc.identifier.uri http://repositorio.unicauca.edu.co:8080/xmlui/handle/123456789/1593
dc.description.abstract Network Function Virtualization (NFV) is an emerging solution that improves the flexibility, efficiency, and manageability of networks by leveraging virtualization and cloud computing technologies to run networked devices in software. The implemen-tation of NFV presents issues such as the introduction of new software components, bottleneck performance and monitoring of hidden traffic. A considerable amount of NFV traffic is invisible using traditional monitoring strategies because it does not hit a physical link. The implementation of autonomous management and supervised algorithms of Machine Learning (ML) become a key strategy to manage this hidden traffic. In this undergraduate work, we focus on analyzing NFV traffic features in two test environments with different components and traffic generation. We perform a benchmarking of the performance of supervised ML algorithms concerning its efficiency; considering that the efficiency of the algorithms depends on the trade-off between the time-response and the precision achieved in the classification. The results show that the NaiveBayes and C4.5 algorithms reach values greater than 90.68 % in a response time range between 0.37 sec and 3 sec. eng
dc.language.iso eng eng
dc.publisher Universidad del Cauca spa
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject IP e
dc.subject NFV eng
dc.subject Networks eng
dc.subject Traffic eng
dc.subject Machine Learning eng
dc.title Autonomic classification of IP traffic in an NFV-based network eng
dc.type Trabajos de grado spa
dc.rights.creativecommons https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.type.driver info:eu-repo/semantics/bachelorThesis
dc.type.coar http://purl.org/coar/resource_type/c_7a1f
dc.publisher.faculty Facultad de Ingeniería Electrónica y Telecomunicaciones  spa
dc.publisher.program Ingeniería Electrónica y Telecomunicaciones spa
dc.rights.accessrights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion
dc.coar.version http://purl.org/coar/version/c_970fb48d4fbd8a85
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