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In recent years the new vision of data-centric networks has emerged as a natural way to satisfy user needs in the Future Internet. It is based on novel architectures oriented towards data sharing and delivering as opposite to classic host-to-host interactions. Among several proposals, Content Centric Networking has been conceived as a very promising solution by the Palo Alto Research Center team. It can be gradually deployed over the Internet and solves different problems, as NAT Traversal, depletion of IP addresses, security, mobility, and multicast communications. In this talk an analytical framework for Content Centric Networks is described, with a particular focus on fairness in cache usage. It captures the distribution of content replicas among nodes of the network by taking into account contents availability, data popularity, topology information, and cache size, thus helping future developments and upgrades on the current CCN architecture. At the same time, the model under investigation merits an extensive future research to complement its main findings with already existing approaches, to deeply inspect both transient behaviors and system stability, and to devise novel strategy layers based on its properties.
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