Optimal privacy preservation strategies with signaling Q-learning for edge-computing-based IoT resource grant systems.

•Propose a privacy-preservation signaling game for edge-based IoT networks.•Obtain optimal privacy preservation strategies from theoretical and practical views.•Address the problem of obtaining the convergent game equilibrium in practice.•Have a lower computational complexity available to real-life implementation.