Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approach

The development of mobile devices with improving communication and perceptual capabilities has brought about a proliferation of numerous complex and computation-intensive mobile applications. Mobile devices with limited resources face more severe capacity constraints than ever before. As a new concept of network architecture and an extension of cloud computing, Mobile Edge Computing (MEC) seems to be a promising solution to meet this emerging challenge. However, MEC also has some limitations, such as the high cost of infrastructure deployment and maintenance, as well as the severe pressure that the complex and mutative edge computing environment brings to MEC servers. At this point, how to allocate computing…

• NN
  National Natural Science Foundation of China

  Awards: 61771374, 61601357, 61771373, 61801360
• FR
  Fundamental Research Funds for the Central Universities

  Awards: JB181506, JB181508, JB171501, JB181507