Recent advances in networking, caching, and computing have significant impacts on the developments of smart cities. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on smart cities. In this article, we propose an integrated framework that can enable dynamic orchestration of networking, caching, and computing resources to improve the performance of applications for smart cities. Then we present a novel big data deep reinforcement learning approach. Simulation results with different system parameters are presented to show the effectiveness of the proposed scheme.

Software-Defined Networks with Mobile Edge Computing and Caching for Smart Cities: A Big Data Deep Reinforcement Learning Approach