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In mobile social networks, forwarding is a challenging problem since there may be no end-to-end paths. Existing schemes using overlays are not applicable to pure mobile social networks since they use environments different from the mobile social networks. To resolve this problem, we propose a novel forwarding scheme that considers the common neighbor similarity and contact probability. In the proposed scheme, the more nodes have in common, the more likely they are to be friends, and higher contact probabilities between nodes increase the chances they will arrive at the destination. The proposed scheme constructs an overlay using two layers with the common neighbor similarity and the contact probability and forwards messages to the destinations through the overlay. Experimental results show that the proposed scheme outperforms most known forwarding schemes in terms of balancing the network traffic and transmission delay. [ABSTRACT FROM AUTHOR]

We study a forwarding strategy in opportunistic networks which are one of the most challenging networks among mobile ad-hoc networks. In opportunistic networks, a node does not have knowledge about the entire network topology, which is essential in the mobile ad-hoc network's forwarding strategy. Thus, node behavior is exploited to calculate future contact opportunities for forwarding a message. Utilizing social network analysis (e.g., similarity and centrality) has been proposed to improve the accuracy of the calculation task. This paper proposes a forwarding strategy based on an analysis of network topology. In the proposed strategy, each node takes a sequence of snapshots of its first-order neighbors during a warm-up period. Each node exchanges its own snapshots with each other, and then aggregates the snapshots in order to extract the network topology information. The extracted network topology is analyzed by social network analysis methods: compactness and algebraic connectivity. Forwarding decisions are made using the analysis of the features (compactness and algebraic connectivity). We present simulations using NS-2 and the home-cell community-based mobility model to show that the proposed forwarding strategy results in delay performances similar to the epidemic forwarding scheme, while maintaining reasonable network traffic. In addition, we demonstrate that the proposed strategy outperforms the SimBet and PRoPHET forwarding schemes with various communication ranges and memory space. [ABSTRACT FROM AUTHOR]

Clustering has been shown to be a highly effective way to reduce network traffic in mobile ad hoc networks. Many clustering schemes have been proposed. However, none of these schemes can be directly applied to a mobile social network because they are designed for well-connected networks and require timely information sharing among the nodes. In this paper, we propose the hierarchical clustering-based forwarding scheme (HCS), which implements hierarchical clustering on social information. Each node constructs hierarchical clusters based on common neighbor similarity at the end of the warm-up period. The nodes then forward a message to other nodes based on the clustering information and similarity scores. HCS exploits the shortcuts on the path toward the destination node with the help of social similarity and node movement patterns. Experiments were performed on an NS-2 network simulator. The results show that HCS reduces network traffic compared to non-clustering schemes, such as Epidemic, SimBet, PRoPHET, and common neighbor similarity schemes, while maintaining acceptable transmission delay compared to the Wait scheme. [ABSTRACT FROM AUTHOR]