Integrated Networking, Caching, and Computing for Connected Vehicles: A Deep Reinforcement Learning Approach

The developments of connected vehicles are heavily influenced by information and communications technologies, which have fueled a plethora of innovations in various areas, including networking, caching, and computing. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on vehicular networks. In this paper, we propose an integrated framework that can enable dynamic orchestration of networking, caching, and computing resources to improve the performance of next generation vehicular networks. We formulate the resource allocation strategy in this framework as a joint optimization problem, where the gains of not only networking but also caching and…

• NN
  National Natural Science Foundation of China

  Awards: 61671101, 61771089
• FR
  Fundamental Research Funds for the Central Universities

  Award: DUT17JC43