Human Mobility Models for Opportunistic Networks

Mobile ad hoc networks (MANETs) enable communications between clouds of mobile devices without the need for a pre-existing infrastructure. One of their most interesting evolutions are Opportunistic Networks (OppNets), whose goal is to enable communication also in disconnected environments, where the general absence of an end-to-end path between the sender and the re- ceiver impairs communication when legacy MANET networking protocols are used. The key idea of OppNets is that the mobility of nodes helps the delivery of messages, because it may connect, asynchronously in time, otherwise disconnected subnetworks. This is especially true for networks whose nodes are mobile devices (such as smartphones and tablets) carried by human users, which is the typical OppNets scenario. In such a network where the movements of the communicating devices mirror those of their owners, nding a route between two disconnected devices implies uncovering habits in human movements and patterns in their connectivity (i.e., frequencies of meetings, average duration of a contact, etc.), and exploiting them to predict future encounters. Therefore, there is a challenge in studying human mobility, speci cally in its application to OppNets research. In this paper we review the state of the art in the eld of human mobility analysis and present a survey of mobility models. We start from reviewing the most considerable ndings regarding the nature of human movements, which we classify along the spatial, temporal, and social dimensions of mobility.We discuss the shortcomings of the existing knowledge about human movements and we extend it with the notion of predictability and patterns. We then survey existing approaches to mobility mod- eling and t them into a taxonomy that provides the basis for a discussion on open problems and further directions for research on modeling human mobility.