An Intelligent Computation Demand Response Framework for IIoT-MEC Interactive Networks

Abstract

The joint optimization problem of a 5G-inspired IIoT-MEC interactive network aims to maximize revenue of MNOs and minimize IIoT operators' economic cost is formulated, which is challenging to be solved. This letter proposes a dynamic pricing strategy for IIoT-MEC network to maximize MNOs' revenue while providing acceptable service prices for IIoT mobile devices (MDs). The dynamic pricing problem is first modeled as a discrete finite Markov decision process (MDP). Then Q-learning algorithm is utilized to solve this problem. The results show that the proposed dynamic pricing strategy can significantly enhance MNOs' revenue and decrease IIoT operators' economic cost.