Characterizing opportunistic communication with churn for crowd-counting

Abstract

In opportunistic networking, characterizing contact patterns between mobile users is essential for assessing feasibility and performance of opportunistic applications. There has been significant efforts in deriving this characterization, based on observations and trace analyses; however, most of the findings arise from studying contact opportunities at large spatial and temporal scales. Moreover, the user population is considered to be constant: no users can join or leave the system. Yet, there are many examples of scenarios which do not fully adhere to the previous assumption and cannot be accurately described at large scales. Urban environments, such as smaller city districts, are characterized by highly dynamic user populations. We believe that scenarios with varying population requires further investigation. In this paper, we present a novel modeling approach to study operation of opportunistic applications in scenarios where the population size is subjected to frequent changes, that is, it exhibits churn. We also propose an application for estimating the size of a mobile crowd, which we then use to validate our model in four scenarios: a city area, subway station, a conference and a scenario with a synthetic mobility model. We show that the model provides good representations of the investigated scenarios.