Abstract—Distributed online social networks (DOSN) have been proposed as an alternative to centralized Online Social Networks (OSN). In contrast to centralized OSN, DOSNs do not have central repository of all user data, neither impose control regarding how users data will be accessed. Therefore, users can keep control of their private data and are not at the mercy of the social network providers. However, one of the main problems in DOSNs is how to efficiently disseminate social updates among peers. In our previous work, we proposed Social Caches for social updates dissemination in DOSN. However, the selection of social caches requires knowledge about the entire social graph. In this paper, we propose four fully distributed social cache selection algorithms, and evaluate their performance on five well known graphs. Using simulations we show that these algorithms perform almost as good as the centralized best known approximation algorithm would do. These distributed caching techniques can be used as a basis for various applications such as those that represent fusions of social and vehicular networks. I.

Recent years have witnessed an explosive growth of the Online Social Networks (OSNs), which serve as a fertile ground for research such as, examining individual and group behaviors, identifying information dissemination patterns, and building unconventional OSNs. This dissertation explores the design and implementation of two emerging OSNs, a distributed social network (DOSN) and a vehicular social network (VSN), both from theoretical and practical perspectives, with the goal of improving the performance and functionality of the systems. Distributed OSNs have been proposed as an alternative to centralized OSNs. DOSNs neither have central repository of all user data, nor they impose control regarding how the data will be accessed, hence, enable users to keep control of their private data. One of the critical challenges in building DOSNs is the performance of the distributed social update dissemination. To address this, we propose Social Caches, nodes that cache updates of their friends in order to reduce the number of peer-to-peer network connections. We formulate social cache selection as an instance of the Neighbor-Dominating Set Problem, and propose a set of approximation, regression and heuristic social cache selection algorithms to solve it. Performance evaluation based on real social traffic data and five well-known social graphs shows that the proposed

Social Networks have gained major popularity and they are part of everyday life for many people in the world. Social networks are usually based on the idea that you create a net-work of trust by friending with people you trust. The trusty mechanisms of social networks could have applications in other websites e.g. when you need to evaluate if a person is genuine and trustworthy and not part of a joint fraud. Also trusty mechanisms have applications in social networks them selves. This paper explores the trusty mechanisms in social networks and their applications outside and inside the net-work. We evaluate the current possibilities and shortcom-ings of social networks. Finally we propose what possibil-ities there is to make the trusty mechanisms more accurate and how to overcome the problem of joint fraud associated to social networks.