Network monitoring applications (e.g., anomaly detection and traffic classification) are among the first sources of big data. With the advent of algorithms and frameworks able to handle datasets of unprecedented scales, researchers and practitioners have the opportunity to face network monitoring problems with novel data-driven approaches. This section summarizes the state of the art on the use of big data approaches for network monitoring. It describes why network monitoring is a big data problem and how the big data approaches are assisting on network monitoring tasks. Open research directions are then highlighted.

Big Data in Computer Network Monitoring / Drago, Idilio; Mellia, Marco; D’Alconzo, Alessandro. - ELETTRONICO. - (2018), pp. 1-8. [10.1007/978-3-319-63962-8_26-1]

Big Data in Computer Network Monitoring

Drago, Idilio;Mellia, Marco;
2018

Abstract

Network monitoring applications (e.g., anomaly detection and traffic classification) are among the first sources of big data. With the advent of algorithms and frameworks able to handle datasets of unprecedented scales, researchers and practitioners have the opportunity to face network monitoring problems with novel data-driven approaches. This section summarizes the state of the art on the use of big data approaches for network monitoring. It describes why network monitoring is a big data problem and how the big data approaches are assisting on network monitoring tasks. Open research directions are then highlighted.
978-3-319-63962-8
978-3-319-63962-8
Encyclopedia of Big Data Technologies
File in questo prodotto:
File Dimensione Formato  
enc_bigdata.pdf

non disponibili

Descrizione: versione camera ready
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 175.88 kB
Formato Adobe PDF
175.88 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2702692
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo