<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Bermudez</style></author><author><style face="normal" font="default" size="100%">Stefano Traverso</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Maurizio Munafo'</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Distributed Architecture for the Monitoring of Clouds and CDNs: Applications to Amazon AWS</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transactions on Network and Service Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amazon</style></keyword><keyword><style  face="normal" font="default" size="100%">AWS</style></keyword><keyword><style  face="normal" font="default" size="100%">CDNs</style></keyword><keyword><style  face="normal" font="default" size="100%">Clouds</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">In press</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Clouds and CDNs are systems that tend to separate the content being requested by users from the physical servers capable of serving it. From the network point of view, monitoring and optimizing performance for the traffic they generate is a challenging task, given the same resource can be located in multiple places, which can in turn change at any time. The first step in understanding Cloud and CDN systems is thus the engineering of a monitoring platform. In this paper, we propose a novel solution which combines passive and active measurements, and whose workflow has been tailored to specifically characterize the traffic generated by Cloud and CDN infrastructures. We validate our platform by performing a longitudinal characterization of the very well known Cloud and CDN infrastructure provider Amazon Web Services (AWS). By observing the traffic generated by more than 50,000 Internet users of an Italian ISP, we explore the EC2, S3 and CloudFront AWS services, unveiling their infrastructure, the pervasiveness of web-services they host, and their traffic allocation policies as seen from our vantage points. Most importantly, we observe their evolution over a two- year long period. The solution provided in this paper can be of interest for i) developers aiming at building measurement tools for Cloud Infrastructure Providers, ii) developers interested in failure and anomaly detection systems, and iii) third-party SLA certificators who can design systems to independently monitor performance. At last, we believe the results about AWS presented in this paper are interesting as they are among the first to unveil properties of AWS as seen from the operator point of view.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">P. Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mini-IPC: A Minimalist Approach for HTTP Traffic Classification using IP Addresses</style></title><secondary-title><style face="normal" font="default" size="100%">4th International Workshop on Traffic Analysis and Classification, TRAC 2013</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CDNs</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">IP Addressing Space</style></keyword><keyword><style  face="normal" font="default" size="100%">Mobile Networks' Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">Traffic Classification and Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The popularity of web-based services and multimedia applications like YouTube, Google Web Search, Facebook, and a bewildering range of Internet applications has taken HTTP back to the pole position on end-user traffic consumption. Today’s Internet users exchange most of their content via HTTP. In this paper we address the problem of on-line HTTP traffic classification from network measurements. Building on the results provided by HTTPTag, a flexible system for on-line HTTP classification, we present and explore Mini-IPC. Mini-IPC is a minimalist approach for classifying HTTP flows using only the IP addresses of the servers hosting the corresponding content. Using one full week of HTTP traffic traces collected at the mobile broadband network of a major European ISP, we investigate to which extent the most popular HTTP-based services are hosted by well-defined sets of IP addresses, and evaluate the performance of Mini-IPC to classify these services using IPs only.&lt;/p&gt;</style></abstract></record></records></xml>