Fog Node Resource Allocation in Fog-Cloud Systems Using Reinforcement Learning

This research paper presents a new method focused on resource allocation in Fog computing systems. We propose an approach based on reinforcement learning that aims to maximize the utilization of Fog resources. By formulating the problem as a Markov Decision Process (MDP), we effectively address the complexities and uncertainties present in Fog computing systems. Through experimental evaluations, the results show the potential of our approach to enhance resource allocation in Fog computing environments.