<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Alessandro D’Alconzo</style></author><author><style face="normal" font="default" size="100%">Pedro Casas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing Web Services Provisioning via CDNs: The Case of Facebook</style></title><secondary-title><style face="normal" font="default" size="100%">5th International Workshop on TRaffic Analysis and Characterization</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Akamai</style></keyword><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Facebook</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">mobile networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Nicosia, Cyprus</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Today’s Internet consists of massive scale web&amp;nbsp;services and Content Delivery Networks (CDNs). This paper sheds&amp;nbsp;light on the way major Internet-scale web services content is&amp;nbsp;hosted and delivered. By analyzing a full month of HTTP traffic&amp;nbsp;traces collected at the mobile network of a major European ISP,&amp;nbsp;we characterize the paradigmatic case of Facebook, considering&amp;nbsp;not only the traffic flows but also the main organizations and&amp;nbsp;CDNs providing them. Our study serves the main purpose of&amp;nbsp;better understanding how major web services are provisioned&amp;nbsp;in today’s Internet, paying special attention to the temporal&amp;nbsp;dynamics of the service delivery and the interplays between the&amp;nbsp;involved hosting organizations. To the best of our knowledge, this&amp;nbsp;is the first paper providing such an analysis in mobile networks.&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%">Zied Ben-Houidi</style></author><author><style face="normal" font="default" size="100%">Giuseppe Scavo</style></author><author><style face="normal" font="default" size="100%">Samir Ghamri-Doudane</style></author><author><style face="normal" font="default" size="100%">Alessandro Finamore</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></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gold mining in a River of Internet Content Traffic</style></title><secondary-title><style face="normal" font="default" size="100%">6th International Workshop on Traffic Monitoring and Analysis, TMA</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Content mining</style></keyword><keyword><style  face="normal" font="default" size="100%">HTTP Traffic</style></keyword><keyword><style  face="normal" font="default" size="100%">URL extraction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">With the advent of Over-The-Top content providers
(OTTs), Internet Service Providers (ISPs) saw their portfolio of
services shrink to the low margin role of data transporters. In
order to counter this effect, some ISPs started to follow big OTTs
like Facebook and Google in trying to turn their data into a
valuable asset. In this paper, we explore the questions of what
meaningful information can be extracted from network data, and
what interesting insights it can provide. To this end, we tackle
the first challenge of detecting “user-URLs”, i.e., those links that
were clicked by users as opposed to those objects automatically
downloaded by browsers and applications. We devise algorithms
to pinpoint such URLs, and validate them on manually collected
ground truth traces. We then apply them on a three-day long
traffic trace spanning more than 19,000 residential users that
generated around 190 million HTTP transactions. We find that
only 1.6% of these observed URLs were actually clicked by users.
As a first application for our methods, we answer the question
of which platforms participate most in promoting the Internet
content. Surprisingly, we find that, despite its notoriety, only 11%
of the user URL visits are coming from Google Search.
</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%">Pedro Casas</style></author><author><style face="normal" font="default" size="100%">Pierdomenico Fiadino</style></author><author><style face="normal" font="default" size="100%">Arian Bär</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IP Mining: Extracting Knowledge from the Dynamics of the Internet Addressing Space (BEST PAPER AWARD)</style></title><secondary-title><style face="normal" font="default" size="100%">25th International Teletraffic Congress, ITC 25</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Content Delivery Networks</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%">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;Going back to the Internet of one decade ago, HTTP-based content and web services were provided by centralized or barely distributed servers. Single hosts providing exclusive services at fixed IP addresses was the standard approach. Current situation has drastically changed, and the mapping of IPs to different content and services is nowadays extremely dynamic. The adoption of large CDNs by major Internet players, the extended usage of transparent content caching, the explosion of Cloud-based services, and the decoupling between content providers and the hosting infrastructure have created a difficult to manage Internet landscape. Understanding such a complex scenario is paramount for network operators, both to control the traffic on their networks and to improve the quality experienced by their customers, specially when something goes wrong. Using a full week of HTTP traffic traces collected at the mobile broadband network of a major European ISP, this paper studies the associations between web services, the hosting organizations-ASes, and the content servers' IPs. By mining correlations among these, we extract useful insights about the dynamics of the IP addressing space used by the top web services, and the way content providers and hosting organizations deliver their services to the mobile endusers. The extracted knowledge is applied on two specific use-cases, the former on hosting and service delivery characterization, the latter on automatic IP-based HTTP services classification.&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>