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.

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Mesh networks conveniently complement infrastructurebased networks, allowing devices to spontaneously form a network and connect with other networks. However, effective service provisioning requires a network monitoring solution with adequate support for topology data dissemination and diagnosis, due to the underlying network dynamics and the absence of pre-existing network infrastructure. In addition, monitoring systems have to face a number of challenges relating to autonomy, robustness and scalability. To this end, we have created a self-organised management overlay that homogeneously and dynamically organises devices into a cluster-based hierarchy on which monitored data is disseminated. Scalability of the monitoring system is achieved through the minimisation of the generated traffic, as a result of the optimised design. We have implemented the proposed monitoring system and evaluated through experiments the resulting performance.

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