  Socially aware networking (SAN) exploits social characteristics of mobile
users to streamline data dissemination protocols in opportunistic environments.
Existing protocols in this area utilized various social features such as user
interests, social similarity, and community structure to improve the
performance of data dissemination. However, the interrelationship between user
interests and its impact on the efficiency of data dissemination has not been
explored sufficiently. In this paper, we analyze various kinds of relationships
between user interests and model them using a layer-based structure in order to
form social communities in SAN paradigm. We propose Int-Tree, an Interest-Tree
based scheme which uses the relationship between user interests to improve the
performance of data dissemination. The core of Int-Tree is the interest-tree, a
tree-based community structure that combines two social features, i.e. density
of a community and social tie, to support data dissemination. The simulation
results show that Int-Tree achieves higher delivery ratio, lower overhead, in
comparison to two benchmark protocols, PROPHET and Epidemic routing. In
addition, Int-Tree can perform with 1.36 hop counts in average, and tolerable
latency in terms of buffer size, time to live (TTL) and simulation duration.
Finally, Int-Tree keeps stable performance with various parameters.
