The goal of this paper is to analyze existing simulation engines and assess how well-suited they are for simulating the formation, existence and dissolution of dynamic social networks, with a special emphasis on networks formed around crowdsensing efforts. The crowd in this context is a loosely-coupled social network of people, who use their mobile devices to collect and share data and receive some sort of service or satisfaction in return. Often it is hard to predict whether users would like a certain future crowdsensing application, therefore it is necessary to simulate the expected behavior of the crowd in a pre-specified simulation environment. This paper proposes an urban parking scenario, in which the drivers collect and share parking related events. The main part of this research is the analysis of three simulation engines, which will show which is the best suited for simulating dynamic social networks formed around crowdsensing efforts. The results will show that there are generic simulation environments capable of simulating large crowds, which also possess suitable visualization tools and integration with geospatial data
