The emergence of Delay Tolerant Networks (DTNs) has culminated in a new generation of wireless networking. We focus on a type of human-to-human communication in DTNs, where human behaviour exhibits the characteristics of networks by forming a community. We show the characteristics of such networks from extensive study of realworld human connectivity traces. We exploit distributed community detection from the trace and propose a Socio-Aware Overlay over detected communities for publish/subscribe communication. Centrality nodes have the best visibility to the other nodes in the network. We create an overlay with such centrality nodes from communities. Distributed community detection operates when nodes (i.e. devices) are in contact by gossipping, and subscription propagation is performed along with this operation. We validate our message dissemination algorithms for publish/subscribe with connectivity traces.

In opportunistic networks, communities of mobile entities may be utilized to improve the efficiency of message forwarding. However, identifying communities that are dynamically changing in mobile environment is non-trivial. Based on random walk on graphs, in this paper we present a community detection algorithm that takes into account the aging and weight of contacts between mobile entities. Our idea originates from message-forwarding operations in opportunistic networks. We evaluate the algorithm on both computer-generated networks and real-world human mobility traces. The result shows that our proposed algorithm can find the communities and detect the changes in their structures over time.