A method for analyzing a content delivery network. The method includes obtaining network traffic flows corresponding to user nodes accessing contents from a set of servers of the content delivery network, extracting a timing attribute from each network traffic flow associated with a server, where the timing attribute is aggregated into a timing attribute dataset of the server based on all network traffic flows associated with the server, generating a statistical measure of the timing attribute dataset as a portion of a feature vector representing the server, where the feature vector is aggregated into a set of feature vectors representing the set of servers, analyzing the set of feature vectors based on a clustering algorithm to generate a set of clusters, and generating, based on the set of clusters, a representation of server groups in the content delivery network.
Unsupervised methodology to unveil content delivery network structures / Giordano, Danilo; Traverso, Stefano; Mellia, Marco; Grimaudo, Luigi; Baralis, ELENA MARIA; Tongaonkar, Alok; Saha, Sabyasachi; Nucci, Antonio. - (2017).
Unsupervised methodology to unveil content delivery network structures
GIORDANO, DANILO;TRAVERSO, STEFANO;MELLIA, Marco;BARALIS, ELENA MARIA;
2017
Abstract
A method for analyzing a content delivery network. The method includes obtaining network traffic flows corresponding to user nodes accessing contents from a set of servers of the content delivery network, extracting a timing attribute from each network traffic flow associated with a server, where the timing attribute is aggregated into a timing attribute dataset of the server based on all network traffic flows associated with the server, generating a statistical measure of the timing attribute dataset as a portion of a feature vector representing the server, where the feature vector is aggregated into a set of feature vectors representing the set of servers, analyzing the set of feature vectors based on a clustering algorithm to generate a set of clusters, and generating, based on the set of clusters, a representation of server groups in the content delivery network.| File | Dimensione | Formato | |
|---|---|---|---|
| US9686173B1.pdf accesso aperto 
											Descrizione: versione ufficiale
										 
											Tipologia:
											2. Post-print / Author's Accepted Manuscript
										 
											Licenza:
											
											
												Pubblico - Tutti i diritti riservati
												
												
												
											
										 
										Dimensione
										345.41 kB
									 
										Formato
										Adobe PDF
									 | 345.41 kB | Adobe PDF | Visualizza/Apri | 
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2675458
			
		
	
	
	
			      	Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
