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The current Internet scenario is very different from that envisioned in the original plan. The original protocols of the Internet were designed to allow simple communications between a few hundreds of academic and government users, which were assumed to be fixed and trusted. Today, a wide range of new access technologies have been introduced, which make user mobility and ubiquitous access easier and widely adopted. On the other hand, new applications and services are spreading, some of which are becoming almost necessary for our life. This new scenario poses several challenges to the Internet infrastructure, and different approaches have been proposed in literature towards the Future Internet. Adopting an evolutionary approach, in this thesis we provide contributions in the area of space and time diversity at IP layer, aiming to overcome limitations of current Internet infrastructure. In particular, we propose new techniques implementing what we call informed diversity: space and time diversity using information about the status of the network to make informed decisions about the operating parameters. We adopt a methodology composed of theoretical, simulations, and experimental analysis, and we provide contributions in terms of methodologies and techniques for network monitoring, and in terms of innovative techniques and tools for space and time diversity at IP layer. Obtained results show that informed space and time diversity achieve better performance than traditional techniques.

Part 4: Security ; International audience ; Censorship is becoming increasingly pervasive on the Internet, with the Open Net Initiative reporting nearly 50 countries practicing some form of censorship. Previous work has reported the existence of many forms of Internet censorship (e.g., DNS tampering, packet filtering, connection reset, content filtering), each of which may be composed to build a more comprehensive censorship system. Automated monitoring of censorship represents an important and challenging research problem, due to the continually evolving nature of the content that is censored and the means by which censorship is implemented. UBICA, User-based Internet Censorship Analysis, is a platform we implemented to solve this task leveraging crowdsourced data collection. By adopting an integrated and multi-step analysis, UBICA provides simple but effective means of revealing censorship events over time. UBICA has revealed the effect of several censorship techniques including DNS tampering and content filtering. Using UBICA, we demonstrate evidence of censorship in several selected countries (Italy, Pakistan, and South Korea), for which we obtained help from local users and manually validated the automated analysis.