Game theoretical analysis of strategy changes and influence factors in Crowdsourcing IoT systems

Crowdsourcing IoT (Crowd-IoT) can improve IoT applications but still faces challenges due to diverse service quality or IoT nodes’ selfishness. For this, numerous studies introduced Game Theory to model Crowd-IoT. However, participants’ strategy selection and influence factors are rarely discussed. Moreover, game players are often considered fully rational and homogeneous (holding symmetric action sets. In this context, we propose an Evolutionary Game (EG) involving four CrowdIoT participants, namely service provider (i.e., worker), service requestor, manager, and platform, to analyze influence factors to strategy changes through both theoretical analysis and numerical results.