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We focus on dissemination of content for delay tolerant applications, (i.e. content sharing, advertisement propagation, etc.) where users are geographically clustered into communities. We propose a novel architecture that addresses the issues of lack of trust, delivery latency, loss of user control, and privacy-aware distributed mobile social networking by combining the advantages of decentralized storage and opportunistic communications. The content is to be replicated on friends' devices who are likely to consume the content. The fundamental challenge is to minimize the number of replicas whilst ensuring high and timely availability. We propose a greedy heuristic algorithm for computationally hard content replication problem to replicate content in well-selected users, to maximize the content dissemination with limited number of replication. Using both real world and synthetic traces, we show the viability of the proposed scheme.

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Opportunistic communication, off-loading and decentrlaized distribution have been proposed as a means of cost efficient disseminating content when users are geographically clustered into communities. Despite its promise, none of the proposed systems have not been widely adopted due to unbounded high content delivery latency, security and privacy concerns. This paper, presents a novel hybrid content storage and distribution system addressing the trust and privacy concerns of users, lowering the cost of content distribution and storage, and shows how they can be combined uniquely to develop mobile social networking services. The system exploit the fact that users will trust their friends, and by replicating content on friends' devices who are likely to consume that content it will be possible to disseminate it to other friends when connected to low cost networks. The paper provides a formal definition of this content replication problem, and show that it is NP hard. Then, it presents a community based greedy heuristic algorithm with novel dynamic centrality metrics that replicates the content on a minimum number of friends' devices, to maximize availability. Then using both real world and synthetic datasets, the effectiveness of the proposed scheme is demonstrated. The practicality of the the proposed system, is demonstrated through an implementation on Android smartphones.