Habit: Leveraging human mobility and social network for efficient content dissemination in Delay Tolerant Networks

This paper proposes Habit, an efficient multi-layered approach to content dissemination in Delay Tolerant Networks (DTN) that leverages information about nodes´ colocation (physical layer) and their social network (application layer). More precisely, the regularity of users´ colocation is learned based on historical colocation observations; also, the users´ social network (or `network of interest´) is dynamically propagated during periods of colocation; finally, these distinct pieces of information are locally combined and used to compute the paths that content should follow, in a way that maximises both precision (i.e., nodes receive only content they are interested in) and recall (i.e., all relevant content is received by interested nodes).