  In this paper, we study two tightly coupled issues: space-crossing community
detection and its influence on data forwarding in Mobile Social Networks (MSNs)
by taking the hybrid underlying networks with infrastructure support into
consideration. The hybrid underlying network is composed of large numbers of
mobile users and a small portion of Access Points (APs). Because APs can
facilitate the communication among long-distance nodes, the concept of physical
proximity community can be extended to be one across the geographical space. In
this work, we first investigate a space-crossing community detection method for
MSNs. Based on the detection results, we design a novel data forwarding
algorithm SAAS (Social Attraction and AP Spreading), and show how to exploit
the space-crossing communities to improve the data forwarding efficiency. We
evaluate our SAAS algorithm on real-life data from MIT Reality Mining and UIM.
Results show that space-crossing community plays a positive role in data
forwarding in MSNs in terms of deliver ratio and delay. Based on this new type
of community, SAAS achieves a better performance than existing social
community-based data forwarding algorithms in practice, including Bubble Rap
and Nguyen's Routing algorithms.
