Evolutionary stable participation game of smartphones in crowdsourced sensing

It is crucial to stimulate active participation of smartphone workers in crowdsourced sensing systems. This is due to the fact that it takes a smartphone worker considerable cost in terms of dedicated smartphone resources, human intervention, and possible privacy breach. Many incentive mechanisms have been proposed. However, existing incentive mechanisms suffer a serious common problem: they all assume full rationality of smartphone worker. Such fully rational smartphone workers are often too idealized! A smartphone worker may not be able to get the complete information and hence fails to compute the optimal strategy. In the real world, however, smartphone workers are usually bounded rational . Being bounded rational, a smartphone worker would not change the current strategy until its utility becomes too low. In this article, we propose an evolutionary stable participation game framework for crowdsourced sensing systems with smartphone workers of bounded rationality. Based on the evolutionary dynamics, we design and implement an evolutionary stable participation mechanism. It is proved that the system converges to an evolutionary equilibrium, which is globally asymptotically stable and robust to any degree of perturbations of the workers. Extensive simulation results show that the evolutionary participation mechanism leads the system to an evolutionary equilibrium quickly.