Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Enrica Sposato"'
Autor:
Giacomo Lanciano, Fabio Brau, Joao Barata, Tommaso Cucinotta, Enrica Sposato, Marco Vannucci, Antonio Ritacco, Antonino Artale
Publikováno v:
Cloud Computing and Services Science
Communications in Computer and Information Science ISBN: 9783030723682
CLOSER (Selected Papers)
Communications in Computer and Information Science ISBN: 9783030723682
CLOSER (Selected Papers)
Detecting anomalous behaviors in a network function virtualization infrastructure is of the utmost importance for network operators. In this paper, we propose a technique, based on Self-Organizing Maps, to address such problem by leveraging on the ma
Autor:
Tommaso Cucinotta, Enrica Sposato, Marco Vannucci, Fabio Brau, Antonio Ritacco, Giacomo Lanciano, Filippo Galli, Antonino Artale, Vincenzo Iannino, Joao Barata
Publikováno v:
CCGRID
Network Function Virtualization (NFV) is the key technology that allows modern network operators to provide flexible and efficient services, by leveraging on general-purpose private cloud infrastructures. In this work, we investigate the performance
Autor:
Tommaso Cucinotta, Enrica Sposato, Giacomo Lanciano, Luca Basili, Marco Vannucci, Antonio Ritacco, Antonino Artale, Joao Barata
Publikováno v:
SAC
In this paper, we propose a mechanism based on Self-Organizing Maps for analyzing the resource consumption behaviors and detecting possible anomalies in data centers for Network Function Virtualization (NFV). Our approach is based on a joint analysis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62b53d512acd045e78296db5fcd4a913
http://hdl.handle.net/11382/533632
http://hdl.handle.net/11382/533632
Autor:
Marco Vannucci, Antonio Ritacco, Giacomo Lanciano, Luca Basili, Tommaso Cucinotta, Antonino Artale, Enrica Sposato, Joao Barata
Publikováno v:
CLOSER
Scopus-Elsevier
Scopus-Elsevier
In this paper, we tackle the problem of detecting anomalous behaviors in a virtualized infrastructure for network function virtualization, proposing to use self-organizing maps for analyzing historical data available through a data center. We propose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b455c580c54a97dd92ed81b2f7befb1
https://hdl.handle.net/11384/131264
https://hdl.handle.net/11384/131264