Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. ness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability.

Online Social Networks (OSNs) are the most popular applications in todays Internet and they have changed the way people interact with each other. Understanding the structural properties of OSNs and in particular, how users behave when they connect to online social networks is crucial for designing user-centered systems. Results about OSNs demonstrated that the relationships that an individual (ego) maintains with other people (alters) can be organised into a set of of circles (named Dunbar's circles) according to the ego network model. In this model, circles are arranged into a hierarchical inclusive sequence based on an increasing level of intimacy. The study of the impact of ego networks structure on the availability patterns of users is seriously limited by the lack of information about users availability patterns. In this work we contribute to fill this gap by analysing availability information of a sample of Facebook users. The data reveal a number of strong temporal dependencies (or temporal homophily) which provide insights into the temporal properties that characterize an ego network.

No abstract

No abstract