On the impact of graph structure on mobility in opportunistic mobile networks

Opportunistic mobile networks are a promising way to offload infrastructure networks, or provide communication in case of insufficient or non-existent infrastructure coverage. Understanding of the mobility process that drives such networks is crucial for design, analysis, and configuration. Generally, this mobility process is modeled on a plain playground where devices can move freely; both in case of simulation, and analysis of real-world traces. Graph-based playgrounds provide more realistic models but their impact on mobility is insufficiently understood. We provide a methodology to analyze the impact of the underlying graph on inter-contact time using methods from spectral graph theory. We gather the inter-contact times that both a random and a social mobility model exhibit on synthetic grid-based graphs and real-world city maps through simulations and perform fitting to a model for inter-contact time distribution. We then analyze correlations between parameters of these distributions and the spectral gap of a graph. Our main finding is that the graph structure has strong impact on inter-contact time distribution in both random and social mobility on grid-based graphs. For real-world city graphs a social mobility model determines inter-contact time independently of the graph structure, whereas the graph structure has strong impact on inter-contact times for a random mobility process.