2017
DOI: 10.18046/syt.v15i42.2539
|View full text |Cite
|
Sign up to set email alerts
|

A benchmarking of the efficiency of supervised ML algorithms in the NFV traffic classification

Abstract: The implementation of NFV allows improving the flexibility, efficiency, and manageability of networks by leveraging virtualization and cloud computing technologies to deploy computer networks. The implementation of autonomic management and supervised algorithms from Machine Learning [ML] become a key strategy to manage this hidden traffic. In this work, we focus on analyzing the traffic features of NFV-based networks while performing a benchmarking of the behavior of supervised ML algorithms, namely J48, Naïve… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 30 publications
(77 reference statements)
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?