Analysis of human mobility patterns for opportunistic forwarding in shopping mall environments

Mobility plays a key role in the forwarding of data in delay-tolerant mobile ad hoc networks, as it is mobility that gives rise to local connection opportunities. Different patterns of mobility may give rise to different opportunity for communication, and different protocols may be more effective in particular situations. It is thus becoming increasingly important to understand user mobility patterns. In this paper, we seek to improve understanding of human mobility patterns in environments having definite and highly organized structure, such as shopping malls. We analyze contact traces between devices carried by people in a medium-scale shopping mall to characterize human mobility in such an environment. This will allow us to design suitable routing algorithms for delay-tolerant network applications for such scenarios as well as to develop and validate a novel mobility model which can be used by the research community to simulate mobile networks in such settings. We show that people’s motion is different according to their relationship to the environment in which they are and present a method to identify individuals expressing different mobility patterns based on delay-tolerant network metrics. From the contact traces, we identify two main groups with different mobility patterns that we name customers and sellers. For these two groups, we observe and quantify mobility characteristics, and present real-world measurement results. Finally, to understand better the role of groups of message carriers expressing different mobility patterns, we perform simulations of a derivative of the Epidemic protocol with real-world mobility traces, which distinguishes between two groups of carriers and entrusts messages through either one or the other. We discuss the implications of our results and make recommendations to guide the design of ad hoc forwarding algorithms for delay-tolerant mobile ad hoc networks in shopping mall environments and to help model realistic simulation scenarios